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This PDF file contains the front matter associated with SPIE Proceedings Volume 7498, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.
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Morphological pattern spectrum was used to shape features description and analysis of visible/near infrared spectra.
Based on the firstly constructed multi-scale Gaussian structure elements, which have similar shape to local feature of
spectra, we calculated pattern spectrums of 10 mineral spectra from USGS mineral spectral library, and then we
compared both the similarity and k-means clustering results of the original spectrum with that of the corresponding
pattern spectrum. The results show that pattern spectrum increases differences between different categories, but retains
similarity within a category, and pattern spectrum is more separable than the original spectra. Mineral spectra
classification has higher accuracy based on pattern spectrum rather than the original spectra.
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To analyze the size and location of the calibration field and the stabilization of systematic error parameters, calibration
field designing for airborne Position and Orientation System (POS) using actual photogrammetric data is discussed in
this paper. The empirical results have verified that a region of 4 strips with 7 images in each strip is appropriate for use as
a calibration field, whose location should be within 1° in longitude from the center of the project. If the equipment is
changed, the POS must be recalibrated. Otherwise, the flight interval of the calibration field should not exceed 30 days.
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High quality images of Earth produced by synthetic aperture radar (SAR) systems have become increasingly
available, however, SAR images are difficult to interpret. Speckle reduction remains one of the major issues in
SAR imaging process, although speckle has been extensively studied for decades. Many reconstruction filters
have been proposed and they can be classified into two categories: multilook and/or minimum mean-square
error (MMSE) despeckling using the speckle model; and maximum a posteriori (MAP) or maximum likihood
(ML) despeckling using the product model. The most well known Lee, Kuan, and Frost filters belong to first
category. These filters are based on conventional techniques that were originally derived for stationary signals,
such as MMSE. In the second category, filters are based on the product model, such as the MAP Gaussian filter
and the Gamma filter, and require knowledge of the a priori probability density function. These filters force
speckle to have nonstationary Gaussian or gamma distributed intensity mean. The speckle filtering is mainly
Bayesian model fitting that optimizes the MAP criteria. Scene reconstruction is performed using an inversion
of the ascending chain. An objective measure is required to compare the technical merits of these filters, and
Shi et al. presented a comparison 15 years ago. In this paper, a brief introduction of speckle, product, and filter
models is summarized. A review of some most widely used SAR image speckle filters is given. And stationary
speckle filters, like Lee, Kuan, and Frost filters, and nonstationary speckle filters like Gamma MAP filter are
studied. Despeckling results on stationary and nonstationary SAR image of these speckle filters are presented.
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Vegetation coverage and its changes are one of the hottest research branches in regional ecological environment change.
An important research content of vegetation coverage is vegetation fraction. Hydropower exploitation cascade in a river
basin inevitably makes vegetation fraction change. In this paper, the sub-pixel decomposition model and NDVI have
been applied to quantitatively estimate vegetation fraction change of Qingjiang River downstream based on remotely
sensed data. The results show that the overall vegetation environment has been greatly improved and the hydropower
cascade development has a greater influence on vegetation fraction change in Qingjiang River basin form 1987 to 2004.
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The goal of this paper is to introduce how to make use of the artificial neural network technique
to develop a new method which can fast recognize atmospheric profiles' characters from hyperspectral
infrared thermal remote sensing. This technique would accelerate the calculation speed of hyperspectral
infrared atmospheric radiative transfer model (RTM). As the launch of hyperspectral infrared sensors such
as Infrared Atmospheric Sounding Interferometer (IASI), it becomes possible for people to take advantage
of the hyperspectral data which contains abundance of precise spectral information, to add constraint
conditions for the researches of some physical models. But in practice, normal hyperspectral infrared
atmospheric RTM are relatively complex and time costing. The calculation speed of these models is not fast
enough to make these models to respond to the variety of atmospheric radiative, or the bright temperature
timely. Therefore, the practical and effective physical models and research methods, such as the practical
surface temperate inversion model, couldn't be founded relay on these transfer models. In order to solve
this problem, institutions and researchers around the world have tried some methods to develop the fast
calculation of atmospheric RTM. But these methods still have problems on speed, accuracy and the
applicability for certain sensors.
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The research was intended to estimate Chl-a concentration of coastal water in Liaodong Bay, China based on reflectance
spectra data collected in situ and satellite hyperspectral
dataHyperion image. After processing and atmospheric
correction, the reflectance of water extracted from Hyperion image can be used to express the spectral characteristics of
different Chl-a concentration. Ratio calculation of reflectance between absorption and reflection peaks of Chl-a, the
derivative analysis of spectrum can greatly improve the correlation with Chl-a concentration. Exponential model of Chl-a
concentration with variable of band ratio between 681nm and 671nm was applied to Hyperion and the mean absolute
percent error is 34% and root mean square error value is 3.30μgl-1.
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A new method for super-resolution reconstruction based on the Gaussian-kernel is presented. Each pixel is modeled as a
Gaussian distribution to reconstruct, which is iterated by the image weighting parameter adaptively. The parallelism of
this real-valued algorithm based on the grid model enables better integration of the information of the low-resolution
images of the same scene. Compared to the bi-cubic interpolation algorithm, experiments show that the proposed
algorithm can achieve a gain up over 1.0dB. The visual quality of presented algorithm demonstrate the recovery of
spatial frequencies above the band-limit and corresponding reduction in ringing artifacts when compared with the bicubic
interpolation algorithm. And the proposed method gets better objective and subjective quality by preserving the
sharpness of the edges.
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Land surface temperature (LST) is one of the key parameters in the atmosphere-land energy and water transfers. An
understanding of the spatial and temporal variations of land surface temperature is important to broad research fields,
including climate, vegetation, hydrology, etc. In this paper, the cloud contamination of MODIS LST product was
analyzed first, and showed that there are numerous data gaps in MODIS 8-day composite LST product, indicating the
necessity of data interpolation. Then the Harmonic Analysis of Time-Series (HANTS) algorithm was applied to the LST
time-series to rebuild cloud-free images and to distill harmonic components. According to the harmonic characters and
reconstruct LST, the spatial and temporal variations of land surface temperature in the Yangtze River Delta were studied.
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Image registration is widely used in remote sensing, medical imaging, computer vision etc. During the last decades,
image acquisition devices have undergone rapid development and growing amount and diversity of obtained images
invoked the research on automatic image registration. There are many methods of registering images in different
research areas. In this paper, the authors a fast automatic image registration based on the self-adaptive triangle constraint.
And the experiment results using this automatic remote sensing registration method based on the self-adaptive triangle
constraint indicate that the method is more distinctive and robust, which results in a higher matching performance and a
better matching efficiency.
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Passive microwave remote sensing was firstly applied to detect the moon by Chang'E-1 satellite with a four channel
microwave radiometer. Its primary goal is to detect the thickness of lunar regolith and to assess the content of 3He. There
are remained theoretical problems to be systematically solved, which include to research the microwave radiation
transfer properties and to establish the suitable model to inverse lunar regolith depth. Considering the variation of these
factors influencing on the brightness temperature, a new multi-layer microwave transfer model to inverse the depth of
lunar regolith is presented. The physical factors among top lunar regolith influencing the brightness temperature change
sharply with the thickness, so the top lunar regolith is divided subtly. On the contrary, the deep lunar regolith where the
factors vary slowly with the thickness is divided roughly. Then, by applying the fluctuation dissipation theorem, the
brightness temperatures obtained from four frequency channels (3.0GHz, 7.8GHz, 19.35GHz, 37GHz) are simulated
based on the multi-layer model at different locations on the moon and at different times of a lunar day. In comparison the
calculated results with other models, it indicates that the proposed model has better stability and less calculation.
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Among most of current Pan-sharpening methods, resampling is generally required to make panchromatic (Pan) and
multispectral (MS) images matched correctly pixel by pixel. However, few methods have focused on spectral distortions
caused by shape distortions of real features during resampling. This paper proposes a new Pan-sharpening algorithm
based on the gray and spectral relationships between Pan, MS and the fused images. In the algorithm, Pan-sharpening is
defined as an optimization of a linear overdetermined system. It takes Pan and original MS images as input datasets
without resampling. The Least square technique is applied to calculate the optimum values (quality fused images).
QuickBird image datasets are tested, and the results are compared with the fused images of IHS, PCA and Gram-Schmidt
using interpolated MS image. The result shows that the proposed method is more efficient than IHS, PCA and
Gram-Schmidt in preserving spectral characteristics and increasing spatial resolution, especially for high spatial
resolution ratio (SRR > 4:1, spatial resolution ratio is the ratio of the spatial resolution of MS image to that of Pan image.) images.
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In June 2008, Enteromorpha prolifra, a kind of green algae, widely distributed in the Surface Water of the Yellow Sea of
China and posed a threat to the 29th Olympic Sailing Games. An 11-channel scanner was used to monitoring the spatial
distribution situation. We will introduce the aerial remote sensing monitoring method in this paper. There are three
objectives. 1) Analyze the spectrum of Enteromorpha prolifra, ocean water and sun glitter in multispectral aerial images;
2) Based on the ground-based and aerial spectrum properties, chose the optimal recognition method and practiced with
software tools; 3) validate the results of aerial remote sensing with field survey. The validation results were preferably
well.
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Many uninhabited islands are far away from the mainland and a lot of management difficulties are caused by above
factors. In order to know the situation of the uninhabited islands clearly and timely, it's necessary to use the remote
sensing to recognize the uninhabited islands. This paper discusses the remote sensing recognition methods of the relevant
characteristics of uninhabited islands based on a wide range of remote sensing data fusion and integration. The first
method is using the combination of TM band data to recognize uninhabited islands. The second method is using the spot
image data to compare with the spatial island layer to recognize uninhabited islands. The results show that they are
effective methods for us to recognize the uninhabited islands and the time could be saved. By contrast, the first method is
a useful complement to location the uninhabited islands but is difficult to get the accurate area. The second method is
important means to get the relatively accurate area of the uninhabited islands. The high resolution imagery is very useful
to recognize the small uninhabited islands and the relatively accurate area could be calculated by overlapped the spatial
island layers.
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The integrated management system of ocean remote sensing data (IMSORS) has recently become more and more
important as the data volume growing exponential, the data diversity increasing, and the developing of the marine
research, and so on. IMSORS evolves into a service-oriented architecture (SOA) that provides the flexibility, multi-scale,
and generality necessary to manage the vast amount of data and applications. Google Earth and web-based GIS are
growing rapidly and used to visualize and share three-dimension (3D) marine environmental data in IMSORS. Google
earth can provide 3D visual and virtual globe for us. IMSORS display the ocean color information in the globe. Webbased
GIS is being used in marine environment visualization, spatial analysis and prediction etc in the IMSORS.
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Linear array CCD push-broom imaging system is adopted by CCD camera of HJ satellite as its imaging system. With the
support of satellite ephemeris, attitude and the knowledge for CCD camera, a rigorous sensor model for CCD image of
HJ satellite is constructed. Meanwhile, an error reduction model based on polynomial transformation using a few GCPs
is used to compensate the positioning error. Experiments show that positioning error is about 185 pixels without GCPs,
and it can be reduced to four pixels when three GCPs are used to compensate the positioning error.
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With the rapid urbanization process, some problem such as unlimited city expansion occurred. When facing these
problems, ever-growing urban data and increasing planning complexity, a scalable, extensible urban planning
supervising and management information system is needed urgently. PlanSuper is such a system that can deal with these
problems. In response to the status and problems in urban planning, the scalability and extensibility of PlanSuper are
introduced which can be seen as business-oriented workflow extensibility, scalability of DLL-based architecture,
flexibility on platforms of GIS and database and so on. It is verified that PlanSuper system has good extensibility and
scalability in supervising and management of urban planning.
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Time lag responses of Gurbantonggut desert vegetation to meteorological factors are analyzed by using
NOAA / AVHRR NDVI time series data from 1982 to 2003 and meteorological factors such as temperature,
precipitation, sunshine hours. Conclusions are drawn as follows: in recent 22 years, NDVI trend in
Gurbantonggut desert is generally upward; its monthly average values are symmetrically presented with a
single peak. From the view of inter-annual changes, annual precipitation, relative humidity, maximum winter
snow depth and NDVI obviously have a positive correlation; annual evaporation, sunshine hours, maximum
frozen soil depth and NDVI significantly have a negative correlation; annual average temperature, ground
temperature and NDVI have no obvious relationship. From the view of different stages of vegetation growing
season, in early and late growing season, vegetation growth and pre-period heat accumulation are closely
related, while vegetation growth and precipitation mostly have a negative correlation. In the middle of
growing season, high temperature will increase water evaporation, vegetation growth is slow due to water
shortage; precipitation and vegetation growth obviously have a positive correlation, its impacts on vegetation
growth is significantly lagging, the previous one and two month precipitation influences vegetation growth
obviously.
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Peak signal-to-noise ratio (PSNR) is commonly used as an objective metric in evaluating image quality. However, PSNR
can not reflect the visual perception distortion, especially for the stereo image in mapping. Meanwhile, the subjective
evaluation methods have great uncertainty. So, how to make correct, effective and repeatable evaluation for the stereo
mapping imagery is still a problem to be resolved. From the aspect of practical mapping application for the stereo
surveying and mapping satellite imagery, a multidimensional model for evaluating the stereo imagery compression
quality is presented in this paper. A new quality assessment index is proposed for decompressed image based on the
model, and by using it, the quality of imagery compressed /decompressed by JPEG and JPEG 2000 algorithm is
evaluated. Experiment results show that using this method can get better consistency with the result from the human
visual perception, and has high correlation with the method of mean opinion score(MOS), superior to the method of
using PSNR.
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Urban ecological parameters, such as land surface emissivity, temperature, and dryness, play important role in urban
ecological system. The present study aimed to explore these ecological parameters using Landsat ETM+ data. The land
surface emissivity (LSE) was calculated from the normalized vegetation index (NDVI) considering different cases; land
surface temperature (LST) was retrieved from the thermal band based on the method of mono-window algorithm; and
land surface dryness (LSD) was derived from the NDVI via LST space, in which the two edges for the minimum and
maximum LST values (LSTmin and LSTmax) were simulated using NDVI values. The results showed that there was an
obvious gradient as progressed from the core city out into the countryside for the three parameters. The values for LST
and LSD over water surface and vegetated surface were obvious lower than that over impervious surface, demonstrating
water and vegetation had the ability to improve environmental quality. These simulation results could provide
quantitative evaluations and suggestions for the environmental planning and management by government.
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Dayao-Wangxian region is located in the noutheastern part of Hunan Province, South China. It is a region of high gold
and lead-zinc mineral potential in China. This article shows the successful implementation of GIS technology for gold
nonferrous metal resource prediction in the subtropical monsoon climate and lush vegetation region. In order to enhance
the credibility of ore-finding, three kinds of information (alteration abnormal, lineament) are extracted from ETM+
image data. By making full use of the geological, geophysical, geochemical, and remote sensing data, we predict 9 first
grade and 5 second grade ore-finding prospective areas in this region. About 90% of the known gold, copper and
antimony mineral occurrences are located in these areas.
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MODIS data are widely used, however, some features that include large data volume and complex storage format
impede MODIS data's direct circulation and use. The introduction of the WCS can improve this situation. In this
paper, on the basis of full analysis of characteristics of MODIS data and WCS, according to OGC WCS
specification, a MODIS data WCS was designed and implemented. Its design idea was expatiated from the logical
framework to the physical structure in accordance with the idea of software engineering. An example was
employed to describe its implement. This article can be a reference for other similar servers' design and
implementation.
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In this paper, we propose a registration method of high-resolution satellite images with geographic coordinates or
rational polynomial coefficients(RPC), which is the relationship between images and ground. Our approach consists of
two steps: firstly, a rough image registration is implemented on the basis of the "correction based on the projection"
theory that is an approximate epipolar line theory. Then, point features and line features in the image extracted by a
combination of corner extraction operators and line feature extraction algorithm will be the elements of the image
matching. A binding triangle net is constituted by all the features extracted to restrict the observed values. And in the end
of the process a high-precision automatic registration is performed by the least squares image matching method.
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Methane (CH4) is regarded as one of the most important greenhouse gases due to its radiative forcing. Since the
SCIAMACHY instrument on ENVISAT was in orbit, CH4 measurements at a regional scale became available. However,
the spatial resolution of 0.5 deg latitude × 0.5 deg longitude omits many detailed spatial variations. The present study
aimed to improve the spatial resolution of the retrieved atmospheric CH4 concentrations with the aid of the normalized
difference vegetation index (NDVI) and land surface temperatures (LST) from MODIS with the spatial resolution of 0.05
deg latitude × 0.05 deg longitude. The gridded CH4 concentrations were firstly converted into point files, which were
then divided into training and testing groups. Three methods of Ordinary Kriging, Regression Kriging, and Co-Kriging
were used to simulate the spatial distribution of CH4 concentrations. The accuracy assessment showed that the
Co-Kriging method combing with NDVI obtained the lowest mean predication error and root mean square prediction
error. Thus, the spatially distributed atmospheric CH4 with the resolution of 0.05 deg latitude ×0.05 deg longitude was
acquired.
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Image registration is required in many remote sensing applications such as multispectral classification, environmental
monitoring, change detection, etc. In this paper, a novel approach of automatic registration of optical remote sensing
images based on SURF (Speed Up Robust Features) and NSNNI (Nearest and Second-Nearest Neighbors Iterative
Matching) is proposed. Using SURF's detector and descriptor, we can generate scale and rotation invariant control points.
Then, the efficient NSNNI method is used to simultaneously find correct matching point pairs and obtain precise
transform model. The results of experiments show that our method can achieve sub-pixel accuracy and satisfy the
real-time demand.
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The purpose of this study is using hyperspectral data to detect the reflectance differences of Chinese fir (Cunninghamia
lanceolata) which are sensitive to acidic stress and have been under different degrees of acid deposition stress for a long
time. The hyperspectral reflectance for Chinese fir leaf is measured by Fieldspec Pro FR under three simulated acid rain
levels (pH2.5, 4.0 and 5.6) during three years in order to monitor the response of leaf. The results indicated: (1)
chlorophyll concentration of Chinese fir increased with the increasing of the simulated rain acidity in the late
experimental period; (2) the 1st derivative values increased at the green edge (480-540nm) and red edge (680-760nm)
with pH increasing; (3) the RVI550 and GNDVI values did differ significantly at pH2.5 and 5.6 treatment; (4) red edge
position was found moving to longer wave bands with increasing rain acidity along with the experimental time; (5) there
are significant differences vale at blue 510nm and 690nm wavelength between different treatments that can be used to be
an useful parameters to distinguish the severity of acid deposition. The research also indicated that the hyperspectral
parameters can be used to monitor the acid rain stress on trees.
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The polarity conversion of oceanic internal solitary waves (ISWs) in the South China Sea (SCS) is studied using
synthetic aperture radar (SAR) images. Eight SAR images which have oceanic internal wave polarity conversion
information in the SCS are selected from about 300 oceanic internal wave SAR images between 1998 and 2008. It is
found that the elevation ISWs mainly occur in the area from 114°E to 115°E longitude and from 20°N to 22°N latitude
during summer and early autumn. All the ISWs propagate westwards with the wavelengths between 300m and 800m.
The polarity conversion is analyzed using one SAR image which contains successive elevation internal waves and the
two-layer KdV theory. Studies with in situ data show that the occurrence of polarity conversion of ISWs in the SCS is
related to a thicker upper mixed layer compared with the lower layer on the continental shelf.
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With the deep understanding and exploitation of the wide Ocean, There are more and more fine instrument installed
or loaded on measuring ships or other marines. The high costs and complexity of corrosion place ever-increasing
demands on the analyses of surrounding ocean environment. In this paper, the fuzzy C-Means clustering is used to
analyze the surrounding ocean environment with remote sensing data. The studied ocean area is considered as a two
dimensional gird or an image, and the fuzzy C-Means clustering technique is used to reveal the underlying relationship
of the elements and segment the interrelated ocean in regions with similar spectral properties in the influence of
instrument corrosion. The influence of the environment elements in instrument corrosion is studied and a priori spatial
information is added to improving the segmentation result. The fitness function containing neighbor information was set
up based on the gray information and the neighbor relations between the pixels. By making use of the global searching
ability of the predator-prey particle swarm optimization, the optimal cluster center could be obtained by iterative
optimization and the segmentation could be accomplished. The calculation results show that the segmentation is accurate
and reasonable. This ocean environment analysis fruit has used in real application and has proved to be valuable in ship
instrument corrosion monitoring and the guide of other ocean activity.
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In this paper, brightness temperature (Tb), normalized difference built-up index (NDBI) and normalized difference
vegetion index (NDVI) were quantitatively derived from Landsat TM images of Beijing City. Feature profiles of Tb,
NDBI and NDVI were drawn in the directions of NE-SW and NW-SE using the technologies of RS and GIS. Laws of
spatial distribution of the relationships between Tb and NDBI, Tb and NDVI were discussed. The results showed that: 1)
there is a significant positive correlation between Tb and NDBI, and a significant negetive correlation between Tb and
NDVI. 2) The less distance between the other profiles and the central profile is, the stronger the negative correlation
between Tb and NDVI is, the stronger the positive correlation between Tb and NDBI is. 3) The relationship between Tb
and NDBI, Tb and NDVI is affected by the complexity of land use structures. The more complex the land use structure is,
the stronger the relationship between Tb and NDBI, Tb and NDVI of feature profile are. This paper effectively reveals the
spatial correlations between temperature and building and vegetion, and thus can provide certain scientific supports for
Beijing's urban and greenland planning in the future.
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Detecting regions of change in multitemporal remote-sensing images of the same scene taken at different times is of
widespread interest in recent years. In this paper, we propose a new change detection method based on a fusion of multisimilarity
measures. This fusion is performed in the framework of the Dempster-Shafer evidence theory, which allows
you to combine evidence from different sources and arrive at a degree of belief (represented by a belief function) that
takes into account all the available evidence. The proposed algorithm is applied to airport change evaluation based on
two popular Gray-textural similarity measures: grayscale difference and grayscale ratio. Experimental results confirm the
effectiveness of the proposed method.
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Based on SPOT images and other geoscience data, this paper gets the land use and land cover information of Modern
Agriculture Corridor from 2006 to 2008 by RS and GIS technology and makes analysis of land use changes in landscape
ecology view. Then we build a quantitative evaluation model which select vegetation coverage as adjustment coefficient
to monitor the changes of ecological services value. The results show that: In the aspect of landscape pattern index, the
landscape heterogeneity of the region is increasing, the land use types become various, degree of landscape
fragmentation has increased; woodland, farmland and construction land play a leading role in the dynamic changes of
landscape. In the view of ecosystem service value, the total value of ecosystem services of Modern Agriculture Corridor
from 2006 to 2008 are respectively 186, 188, 193 million Yuan, and the annual average rate is 2%; ecosystem qualities
are different in different seasons, and quality in summer is best which has 33% contribution to the full-year value of
ecosystem services; the average contribution rates of forest and waters ecosystems are the highest, respectively 37% and
33%; increase of woodland, grassland and water area is the main reason that enhancing ecosystem services.
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Wetlands are among the most important ecosystems on Earth and the major feature of the landscape in almost all parts of
the world, it provides a wide range of ecological regulation services and is very important to the atmospheric humidity in
a region. In order to recognize the influence of wetland on the atmospheric humidity, this paper takes Beijing-Tianjin-
Tangshan region as the study object and quantitatively analyzes their relationship with the help of MODIS satellite
images, monitoring data observed with the ground weather stations, wetland data, and other land surface data. This
research finds that (1) Globe temporal feature of atmospheric humidity is closed to the seasonal change and alternation.
(2) Globe spatial feature of atmospheric humidity is influence by the landform, land cover type. Because study region
adjoins to sea, it is influenced by the distance away from coastline. (3) Wetland's spatial distribution influences with the
spatial distribution of atmospheric humidity. With the distance away from wetland is bigger and bigger, atmospheric
humidity is less and less. However, its change trend is mild.
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This paper focuses on RDF and ontology and semantic-enable geo-spatial data discovery and integration. The Wuhan
administrative semantic model as a part of urban topographical semantic model was firstly proposed to support the
service utilities discovery in the urban area. Based on Oracle 11g semantic tools, the semantic model is stored into
database, and ontology based querying, rule based reasoning, and ontology enable data discovery and integration are
implemented. The experiment results are presented and analyzed in this paper, which show this semantic way can
provide much more flexible, smart discovery ability that the traditional way can't offer, and semantic enable data
discovery and integration has a good application prospect.
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Ecological land layout is a key step of land use planning. Effective ecological land layout could benefit to the
ecology, economy and society. Based on Matlab, a new simple osculating method was introduced in the paper, which
was used to provide the basis for land layout. At the same time, GIS was used to be the technological platform for
dividing land planning unit, managing all data and displaying all land layout planning results. The new planning method
includes 4 steps. Firstly, the land should be divided into many planning units in GIS. Secondly, several planning targets
should be chosen. The third step is to select indicators to be analyzed and to determine their weights. The forth step is to
calculate osculating values and to layout land planning units for different needs. Finally, all the land would be laid out to
satisfy all needs. A case study on Houjie Town was presented to demonstrate the new method. Considering land use types
and the number of requests, the comprehensive ecological land layout planning was ensured. Six pictures in different
colors showed the results of ecological land layout planning on Houjie town.
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Sea surface temperature (SST) and chlorophyll-a concentration (Chl-a) are two typical variables of the ocean
environment. This study focus on the area(120-130°E,22-34°N). The SST and Chl-a are monitored using MODIS data.
the temperature and salinity are observed in situ from Argo. the change of these variables are simulated by COHERENS.
In addition, the Ekman Pumping Velocity(EPV) are calculated. The results are as follows: Firstly, the SST in the study
area before NARI was 27.23°C, from 13th to 18th on Sep in 2007 was 25.65°C with the minimum SST of 24.91°C on
14th during NARI. Secondly, the Chl-a before and after NARI was 0.86mg/m3 and 1.23 mg/m3 respectively. On 5th
day after hurricane, Chl-a reached to 1.95 mg/m3 . These observations of SST and Chl-a basically kept in consistence
with the numerical simulation based on COHERENS in trend. Thirdly, the EPV before NARI was 2×10-5m/s, on the
15th up-to 3.5×10-4 m/s. Finally, the two groups of temperature and salinity data from Argo are on 4th and 14th. The
observations showed that SST dropped from 29.95°C to 28.82°C. The average water temperature of 760 meters depth
was 19.06°C and 17.85°C on 4th and 14th, respectively. The thermoclines were significantly weakened both in the
surface and subsurface layer, the maximum salinity was 34.9psu on 4th near 100 meters and 34.86psu on 14th near the
130 meters depth. The salinity of the halocline decreased because of vertical mixing between the two layers with
low-salt.
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Hyperspectral imaging technology is the foreland of the remote sensing development in the 21st century and is one of the
most important focuses of the remote sensing domain. Hyperspectral images can provide much more information than
multispectral images do and can solve many problems which can't be solved by multispectral imaging technology.
However this advantage is at the cost of massy quantity of data that brings difficulties of images' process, storage and
transmission. Research on hyperspectral image compression method has important practical significance. This paper
intends to do some improvement of the famous KLT-WT-2DSPECK
(Karhunen-Loeve transform+ wavelet
transformation+ two-dimensional set partitioning embedded block compression) algorithm and advances KLT + bands
combination 2DWT + 2DSPECK algorithm. Experiment proves that this method is effective.
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The topological relationship of the spatial data is very vital for addressing GIS data and spatial analysis, because the
topological relationship makes it possible for us to define the spatial location of one geographical object according
another without calculating the distance or using coordinates. Topological relationship built on 2D GIS has been
developed nowadays, however in 3D GIS, there is no mature algorithm about the automatic structuring because of the
complicated topological relationship. After a deep research about the automatic structuring algorithm in 2D surface (we
call it levorotary algorithm), this essay will provide an algorithm based on patches, through which the relationship
between patches and 3D objects will be built automatically, this algorithm lays the basis of spatial query and spatial
analysis.
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Remote sensing data cover large areas and can be acquired in a regular repeatable manner. Automatic land-cover
classification in satellite images is an important topic and has applied in remote sensing widely. In this paper, we
consider Landsat5 Thematic Mapper (TM) data of the Qinghai-Tibet highway of 1986 and 1994 to analyze the changes
of land-cover. Statistics and artificial intelligence method are combined to improve the classification precision. And the
classification result can provide quantitative data for road environment issue, road location selection, and landscape
design.
In this paper, Principal Component Analysis (PCA) is applied to character the main information of TM land-cove
image. Then two neural network models are used to classify the TM image: Back-Propagation Neural Network (BPNN)
and Self-organizing feature map (SOFM) neural network. BP neural network is widely used. Contingency matrix is used
to evaluate the classification precision. By comparing classification accuracy and Kappa quotient, conclusion is drawn
that the classification accuracy of SOFM is higher than BP and MLC and the classification ability of BP is not as good as
MLC. Overall accuracy of SOFM is 94.0%, Kappa is 0.9114, and overall accuracy is 14.9% and 9.8% higher than BP
and MLC. So SOFM is used to classify image of 1986. In the end the land-cover changes of two year are analyzed.
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High resolution image can be used to distinguish the small difference of the ground things. Texture information can
avoid the matter of same spectral from different objective and different spectral with same objective which must be faced
when making classification with only spectral information. The main objective of this research was to determine the
capacity of high spatial resolution satellite image data to discriminate vegetation in urban area. A high spatial resolution
IKONOS image, coincident field data covering the urban area of linping scenic region in Yuhang town, Zhejiang
province in china, was used in this analysis. The vegetation of test region was classified as tea garden, masson pine, fir,
broadleaves, and shrub/herb based on the field data. Semi-variograms were calculated to differentiate vegetation classes
and assess which window sizes were most appropriate for calculation of grey-level co-occurrence texture measures. The
texture analysis showed that co-occurrence mean, variance, contrast, and correlation texture measures provided the most
significant statistical differentiation between vegetation classes. Subsequently, a decision tree classification was applied
to spectral and textural transformations of the IKONOS image data to classify the vegetation. Using both spectral and
textural image bands yielded the good classification accuracy (overall accuracy=81.72%). The results showed that it has
the higher accuracy to extract the urban green space from IKONOS imagery with the spectral and texture information, as
well as the vegetation index.
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A modified fire spread fast model combining CA framework with WangZhengfei's model is proposed for Emergency
Rescue system.This model combines weather condition, terrain slope and vegetation type. It is suit to intricate
topography and environmental southwestern fire-prone areas in China. A grid and vector polygon including the
outermost fire fronts is obtained for GIS spatial inquiring, providing support for Aid in Decision Making. Simulation and
experiments prove cellular automata feasible and effective for fast fire spread model, special in multi-factors restrained
forest fire simulation.
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We introduce a method of urban road network evaluation based on RS and GIS. This method evaluates urban road
network in a real-time, accurate and rapid way. According to scientificity and testability, road network evaluation
indicator system is established with the support of RS and GIS; the current data of urban road network is collected with
Erdas; the urban road data are digitized and organized with powerful MapInfo; Geodatabase of ArcGIS is adopted for
urban road database, and the relevant data is processed in order to extract the information required by road network
evaluation indicator system. The results of urban road network evaluation of a tourist city show that the method can
provide scientific evidence and information support for planning and construction of urban road network.
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The spatial resolution is an important measure about spatial scales, which affects the accuracy of interpretation for
remote sensing imagery and furtherer leads to some serious uncertain problems on fractal model of urban land use. In
this paper, the average local variance model based on spatial sampling method is used to select the appropriate spatial
resolution in order to improve fractal model of urban land use. The information entropy dimension is proposed to
quantitatively express spatial balance for a certain urban land use type. An example of application research is
experimented in Wuchang district through QuickBird remote sensing imagery in 2002. By scaling up with the initial
spatial resolution, the appropriate spatial resolution is 10m in round numbers. The information entropy dimension of
built-up area and water are 1.921 and 1.907, which are larger and imply more homogeneously spatial distribution. But
the information entropy dimension of farmland and unused land are 1.291 and 1.218, which are lower and imply more
concentrated spatial distribution. The results suggest that the average local variance is very advantageous to provide the
appropriate resolution for remote sensing imagery, which can greatly improve the accuracy of interpretation in extracting
feature information of urban land use.
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Land use and forest cover products in highly dynamic tropical ecosystems lack the detail needed for natural resource
management and monitoring at the regional level. The aerial photography provides effective methods to combine local
forest cover data for land cover mapping and land resource management. In this paper we use aircraft imagery at the
regional level over a characteristic location of tropical woodlands in Guangxi, China. The performances of maximum
likelihood classification and Decision tree supervised classification were assessed. The most consistent results were
achieved using decision tree analysis of aircraft images. This method provided better accurate classification for
mangroves, broad-leaved forest, coniferous forest and shrub and the average classification accuracy is above 86%. The
aircraft image provided a more accurate classification for the dense forest cover class. The selection of the right image
dates proved to be critical for different forest type recognition. It make them promising options for rapid and inexpensive
forest cover mapping in regions of high environmental variability such as tropical coastal zone.
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Synthetic Aperture Radar images reveal geometric and radiometric distortions that are caused by terrain undulations. It is
necessary to eliminate the distortions before the measurement of geophysical and biophysical parameters from the SAR
images. The traditional method based on a single SAR image can not totally eliminate the geometric and radiometric
distortions that are caused by variable terrain. In this paper a new intact operation system based on two-looking direction
RADARSAT-2 images is put forward which can eliminate the geometric and radiometric distortions. This new operation
system consists of 4 major steps and is applied to the test area under investigation.
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Soil moisture plays a very vital role in slope failure events because it reduces the soil strength and increases the soil
stress. Traditional in situ surveying cannot provide enough large-scale and so long time soil moisture and precipitation
information; in addition it will takes much time and money. The Tropical Rainfall Measuring Mission (TRMM)
instrument can provides precipitation data from 1997 to present. This paper discuss a active/passive microwave remote
sensing approach to estimate soil moisture using PR and TMI data onboard the TRMM satellite. Then we develop a link
between the soil moisture developed from PR and TMI data, precipitation data and major landslide events in the Three
Gorges of the Yangtze River. Case studies in Three Gorges indicated that most reservoir area of the Three Gorges had
slope movement when soil moisture showed high values.
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The CCD images were obtained during the intensive observation period of the Watershed Allied Telemetry Experimental
Research. 49 scenes of CCD images with 1-m spatial resolution were used for the pre-processed and investigation on the
north suburban wetland resource for the Zhangye City. The pre-processing includes radiometric correction, preliminary
geometric correction, preliminary image mosaicing, offset position processing, color matching, differential GPS
measurement of the Ground Control Points, geometric precision correction. The image mosaicing exists a series of
problems. The biggest problem is the disagreement of the hues. The software of Geoway ColorPro was used to match the
colors. The manual interpretation method was applied to extract the patch boundary and type from the mosaiced image.
Some questionably patch types were confirmed based on the field investigation. Three main conclusions can be obtained
according to the investigation. Firstly, the wetland patches are more fragmentized than the patches of the other land use
types. Secondly, the wetland area occupies 45.8 percentages of the total investigation area. The first three wetland types
are herb swamp, forest and shrub, and Inland salt marsh. Finally, the investigation results were widely applied to the
different departments of the local government.
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The function and services of ecosystem are important components of the life-support system in the planet, as well as the
basic elements for sustainable development of environment and society. In this study, the change of ecosystem function
and services in Jiangxi Province of China were estimated by employing the classification and economic parameters from
Costanza et al. The types and area of terrestrial ecosystems in 1980s and 2000s were identified from Landsat imagery,
based on the maximum likelihood classification methods. And then the distribution maps of ecosystem services of
Jiangxi Province were drawn. The value for terrestrial ecosystem was 2522x108 RMB in 1980s, while it increased by
7.3% in 2000s, which mainly because the increased forest areas in Jiangxi Province. The estimation method employed in
this study was conservative, and should be improved in future studies.
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The factors sensitive to suspended sediment concentration (SSC) with both strong correlation and evident physical
meaning are found step by step with the data collected from Sheyang River estuary. These factors combined by
reflectance of 605 nm, 715 nm and 810 nm which near the reflectance peaks of turbid water have strong correlations
with SSC. The results of the model established by the factor R605xR715/( R605-R810) were consistent well with real
distribution laws of SSC and its relative accuracy arrived over 65%. It shows the advantage of hyperspectral sensors on
monitoring SSC in offshore area.
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The frangibility and vulnerability of Karst ecological environment have induced a series of major ecological
environmental problems in Guizhou province, China. So, it is important to study the Karst landscape pattern in Guizhou
province. In this paper, quantitative remote sensing inversion model and spatial analysis have been selected to study
Karst landscape spatial pattern of Qingzhen city in Guizhou. The results show that the topological relations between
different landscape patterns are very complexity and Qingzhen city has characteristics of high degree Karst landscape
fragmentation and fragile Karst environment. Shrub-tree is a dominant landscape type while severe rock desertification
landscape has strong interference characteristics.
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Image mosaic technology is an important research field of image processing and a research focus on the computer vision
and computer graphics. The traditional method is to select the feature points by manual selection method, which faces
the problem of low reliability and efficiency in the batch of the image mosaic. The SIFT features have many properties
that make them suitable for matching differing images of an object or scene. But the computation amount and the
computation complexity are so great, which restricts the further real time application. So an automatic remote sensing
image mosaic algorithm based on modified SIFT feature is presented in this paper to solve these problems. The method
presented in this paper consisted of three steps: noise removal, modified SIFT feature registration and automatic mosaic.
The test results show the modified mosaic algorithm based on the SIFT feature can improve the matching accuracy and
reduce the computation times.
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Methods for cloud scene simulation are analyzed and studied based on the properties of real cloud edge and distribution
of the atmospheric background radiance. A new method is proposed to simulate cloud scene by means of the fractal
geometry algorithm after effects of clouds on the atmospheric background radiation are analyzed. Firstly, spectral
radiance of cloudless and cloudy atmospheric background is respectively calculated according to the radiative transfer
theory. Secondly, a simulation method for cloud edge is developed based on the improved random generator after
studying the properties of real cloud edge and self-similar character of the fractal principle. Finally, an algorithm
implemented to create cloud texture is designed by employing the radiance distribution of cloudy atmospheric
background, quadric random method and Diamond-Square interpolation. All 2-D atmospheric background radiance
within given view filed has been computed with the mixed modified delta-Eddington approximation method. Some
numerical scenes for cloudy atmospheric background are triumphantly simulated with the radiative transfer theory and
the fractal geometry algorithm.
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This paper presents whole pre-processing streamline of Beijing-1 small satellite images and focuses on some of the key
issues in specific or improved data acquisition and processing. Characteristics of small satellite and peculiarities in the
image pre-processing are analyzed, design and skeleton of the
pre-processing system is expounded, and then, some of the
key issues encountered and explored during processing of Beijing-1 small satellite data are discussed. The discussed
issues include relative calibration, onboard compression, jitter removal and exposure control. The works in this paper are
done with integration exploration based on systematic consideration of whole imaging and processing process, and are
all testified with practical implementation.
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The measurement of the modulation transfer function (MTF) is one of the key steps in characterizing the signal transfer
characteristics of an imaging system as a function of spatial frequency in terms of linear response theory. Various
methods have been proposed to determine the MTF of an imaging system which are based on point, slit or edge images.
The slanted-edge method is the ISO 12233 standard for the MTF measurement of electronic still-picture cameras. In this
paper, the method is modified to avoid amplifying the noise during the derivative computation by performing
curve-fitting. In the experiments, we compare several different analytical function models for the ESF fitting and find
that Logistic (Fermi) function gives the best result.
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Due to the complexity of building composition and imaging condition, urban areas show complicated structural
information in remotely sensed images. On the other hand, the structural information of each site in urban area depends
on that of neighboring sites. In this paper, a discriminative model, conditional random field (CRF), is introduced to learn
the dependencies and fuse the multi-scale textural information to detect urban areas. In addition, because of the
redundancy in structural information, a feature selection method is employed to reduce the dimension of them before
they are put into CRF model, decreasing time consumed in model learning and inferring. By using images of high spatial
resolution as input, experiments are performed, indicating that CRF model outperforms SVM in urban areas detection in
terms of accuracy, and that, through feature selection it can decrease time consumed in model learning and inferring and
obtain competitive result with original data.
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Land use/cover change (LUCC) research is an important research area of global environment change, but the research on
the coal mining area is little. Taking the typical mining city -Jiaozuo City in Henan Province as a case with
multi-temporal remote sensing images as major data resources and combining social and economic statistic data, the
change of land use of Jiaozuo City in recently ten years was systematically studied, and then the ecological
environmental effect caused by land use change was analyzed based on the theories of ecological services value. The
research result shows that the condition in mining city was deteriorating and measures shall be taken to improve
ecological environment. The studied result can provide scientific basis for ecosystem construction and strategic decisions
for sustainable development of mining city.
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Gilson Alexandre Ostwald Pedro da Costa, Flávio Fortes Camargo, Dario Augusto Borges Oliveira, Cláudia Maria de Almeida, Raul Queiroz Feitosa, Rodrigo da Silva Ferreira
Proceedings Volume MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74981K (2009) https://doi.org/10.1117/12.833205
This paper introduces a new open source, knowledge-based platform for automatic image interpretation called
InterIMAGE. The architecture, main features as well as an overview on the interpretation strategy implemented in
InterIMAGE is presented. The paper also reports an experiment based on a Geomorphology application. The
experiment's objective was the automatic identification of geomorphological features using a knowledge model that
considered a set of textural and geomorphometric variables extracted from a digital elevation model obtained from a pair
of stereoscopic ASTER/Terra images. The experiment's results showed a strong agreement between the automatically
classified scene and a reference map. A similar experiment was carried out with a commercial, image interpretation
software - Definiens Professional -, and the results attained with both software packages were comparable.
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LiDAR (Light Detection and Ranging) can provide accurate remote sensing data for extracting surface information, and
large footprint LiDAR has demonstrated great potential for accurately measuring forest canopy characteristics, which are
important for regional and global climate change studies. In this study the Geometric Optical Model, Radiative Transfer
Model and hotspot condition are used to explore the relationship between canopy structure and large footprint LiDAR
return waveforms. A simplified model was simulated, and detailed analysis was made. The model was improved by
adding an extinction coefficient and a scatter coefficient, and then some simplified parameters are introduced to the
model. The new 3D model is simulated by considering the characteristics of large footprint LiDAR and forest stand. The
experiment results show that terrain slop can influence LiDAR return waveform shapes greatly, while tree height just
affects the starting position of waveforms, and the effects of terrain slop and extinction is reduced obviously. The new
model was validated with field data of Changbai Mountain, and the results have good agreement with GLAS data, and
relatively, the improved model and simulation of waveform fit the actual return waveform of large footprint LiDAR
system.
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Powerline vegetation management has been a labor intensive and costly practice for energy companies. This situation
may be improved with use of new positioning and remote sensing technologies. This paper provides reviews and
comparisons for a number of state-of-art powerline extraction and modeling methods using the aerial, radar and
laserscaning images. The prospect and feasibility of powerline surveillance using remote sensing technology are also
presented.
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As a key input parameter in many climate and land-atmosphere models, the validation of retrieved leaf area index (LAI)
on regional scale from remote sensing data makes great senses. The problem of scale between the field experiments and
the ground parameters retrieved from satellites is still one of the most difficult problems in the validation of satellite
remote sensing data. The difficulty is twofold: First, the field measurements are not exhaustive; Secondly, the model is
not linear and surface on satellite pixels is not homogenous. Therefore the objective of the scaling transform study is to
estimate a non-linear function describing spatial distribution information of pixels from information on sub-pixels. The
Computational Geometry Model is a general spatialization method which can realize the scaling of non-linear and
discontinuous function. However it needs a large amount of computing time and a special algorithm to retrieve convex
hull when facing a large number of input arguments. In this paper QuickHull algorithm is introduced to resolve the
scaling problem of the bivariate LAI retrieval function. The scaling effect is analyzed through aggregating the
high-resolution LAI (pixel size of 30 meters) retrieved from TM images by means of CGM method and directly
aggregated method respectively. The CGM method is proved to have the capability of improving the scaling effect of
LAI at larger aggregated scales. It is a prospect method to resolve the scaling problem and will take effect for the
validation with limited field experiments.
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Land cover classification is essential for the monitoring, protecting and managing of wetlands. With Dongting Lake in
Hunan province of China selected as the study area, a scene of hyperspectral image acquired by EO-1 Hyperion was used
to evaluate the methods for land cover classification. After a series of preprocessing including bands removal,
radiometric correction, strip removal and geometric registration, MNF transformation and band selection were adopted
for dimension reducing. Then the image was classified into eight land cover types via MLC, SVM, SAM and MF
classifier. Results reveal that higher classification accuracy would be obtained if data dimension reduction is done by
MNF method. In addition, SVM performs best among the four classifiers, followed with MLC, while SAM and MF
show worse performances.
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This paper presents an improved cooperative matching algorithm based on feature regions. The proposed algorithm uses
normal vector in each pixel position of the whole images to extract the feature regions of image sequences of buildings.
In order to obtain a sparse depth map, matching areas are limited to feature regions rather than whole images. The image
similarity of each pixel is defined as match value. Iteratively update match values and make the match values convergent.
For each pixel, the pixel and disparity which the maximum match value corresponds to are regarded as matching results.
By using feature regions extraction of image sequences, not only can the reconstruction process be further simplified, the
running speed can also be increased. The experimental results show that our method is effective and can avoid
mismatching in some regions which are texture-less or have sparse texture. Meanwhile, the problem of large
computation is solved by pruning unnecessary matching regions.
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In this paper, we developed method to find the suspicious breeding region of oncomelania in Three Gorges reservoir area
based on GIS. Major data used in this study include meteorological data of 56 stations during 1971-2000, hydrological
data of the main channel and tributaries of Changjiang River, and ETM remote sensing data. With the evaluation of
refined meteorological element distribution maps,
water-level-fluctuation zone, vegetation, and other factors, we found
the suspicious breeding region of oncomelania in Three Gorges reservoir area, and selected two focus regions of qukou
in Kaixian and dachang in Wushan for further monitoring.
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In this paper, a progressive texture retrieval algorithm for remotely sensed imagery based on Contourlet spectral
histogram is proposed. Contourlet transform is applied to extract texture features of remotely sensed imagery from
different scales and different directions. Decomposed low-pass subband and high-pass subbands are used to realize
coarse and fine retrieval respectively. The proposed algorithm not only utilizes the advantages of Contourlet on multiscale
and multi-direction feature representation and extraction, but also utilizes the efficiency of spectral histogram on
distributed statistical feature description. Experimental results prove that Contourlet Spectral Histogram provides a
powerful tool for texture retrieval of remotely sensed imagery.
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Earth's surface space is a complex huge system and character with hierarchical structures. Entities, patterns and processes
all show inherent hierarchy structure in nature. The character of Scale-dependence is corresponded with hierarchy. Many
research works have demonstrated that scale-dependence is a basic characteristic of Geo-spatial space. Therefore, the
multi-scale or hierarchical approach needs to be introduced in the course of spatial information analysis, monitoring,
modeling and management. It is well know that image analyze result was influenced by the window size that was
selected. The original fixed window cannot suit with the object spatial character. In this letter, we first propose an
optimal window selection method, based on the spectral information in a local block region, for choosing the suitable
window size adaptively. Secondly, the object spatial information is learned based on the selected optimal window size.
Thirdly, both the spectral and spatial information were used in image classification. In this paper, the proposed algorithm
can obtain the multi-scale features effectively and the features we get at different scale level have an obvious stability
with property. In the experiment on the QuickBird image data, the proposed algorithm clearly improves the classification
accuracies than fixed window sizes and reduces the salt and pepper effect and error. It is suitable to form multi-scale
hierarchy image-sets and select the objects at different scale levels.
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Hydrosphere movement in coastal zone performs as salty and fresh water mutual function. The Longkou city
coastal zone which moves in the humanity under the intervention, has initiated the large-scale sea water intrusion, and
therefore was especially under severe circumstances since 1980s. Until the end of 1980s and the beginning of the 90's,
the sea water intrusion zone has formed the belt which spread fast from several hundred meters to several thousand
meters along the coastal zone of Longkou city. Taking the landsat TM images in 2000 as data sources, first we applied
the principal components transformation and analysis to analyze the six TM wave bands, and then use the histogram
equalizing to deal with them. We use the two-value approach to be possible to remove the villages and small towns, the
path, the pond (fishpond), the vegetables greenhouses, the rivers, the sand very conveniently. We take wave band as the
research band, TM3, TM4 and TM5, which passed through correlation coefficient confirmation. Using the principal
components analysis method to determine vegetation degree of coverage, the bare land index and the green index, the
humidity analyzed in turn as four factors of the sea water intrusion. Inversion model of sea water intrusion is build up
with the four factors. Finally a case study on the Longkou city, the analysis is obtained that the results have a very good
correlation with the field measurements, and in accordance with the extent of the intrusion is divided into four categories.
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In China, the contradiction of urban land use and cultivated land use is predominant, it's important to detect the urban
land use cover for the guide of urban development. The primary problem of dynamic detecting on urban land use cover
is how to get accurate classification of remote sensing data. Theoretically, if combining several low precision classifiers,
a better classification result can be made and this paper introduces how to combine the low precision urban land use
cover classifiers. We use CBERS (China-Brazil Earth Resources Satellite) remote sensing images of the year 2007 for
Shanghai's urban land use cover. We adopt the AdaBoost combination classifier, which combines spectral feature
information, texture structure information and improved Normalized Difference Built-up Index (NDBI) to improve the
individual classification precision. The experiment results show that a notable improvement of classification precision of
urban land use cover is achieved after using AdaBoost algorithm.
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According to the problem of spectra variation inside and spectral mixed on boundary of the farmland in mid-resolution
images, this paper aims at carrying out per-field classification to improve the accuracy of measuring winter wheat plant
area. This paper chooses the urban agriculture region with complex plant structure as experiment area and digitizes the
parcel boundary by QuickBird image. By utilizing the farm parcel as end member, the study extracts the information of
spectrum, vegetation index and texture from multi-temporal TM images. We establish the evaluation system of field
accuracy and total accuracy. The classification methods used in this paper include Support Vector Machine (SVM) and
Maximum Likelihood. The study showed that the per-field classification got higher total accuracy field accuracy and
stability than per-pixel classification when using for winter wheat plant area measuring. It was useful to improve the
accuracy by introducing vegetation index and texture information into per-field classification. The method of both SVM
and maximum likelihood got gross accuracy above to 97% and field accuracy above to 90%. The SVM method was
more stable than maximum likelihood method, and required much smaller size of training samples. So SVM was more
suitable for winter wheat per-field classification. It was useful to improve the accuracy by introducing vegetation index
and texture information into per-field classification. This study could provide a new idea about the remote sensing
measurement of crop planting area.
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At present, with the development of the affection in different layouts and decision-makings of
orthophotomap in various fields, the information quantity of digital orthophoto map reflects and
decides the affection of decision- makings on deep degrees, and it affects the dependability of
analytical result, thereby, to perfect the outputs of digital orthophoto map is a problem that should be
solved as soon as possible . The paper summarizes the current status of the digital orthophoto map,
introduces the backdrop, and analyses the main question in the development of digital orthophoto
map.The paper analyses three contents of information entropy: Shannon-Wiener entropy, Markov
information entropy and Co-occurrence Matrix entropy. Through the experiments we find out that
using Markov information entropy to account the information quantity of orthophoto character on the
digital orthophoto map is the best one. The map load is very important for the map. The paper analyses
the complexity and particularity of the digital orthophoto map laod through the introduction of map
load of general map. It studies on map load based on information and probability,and puts up a test to
try to express the map load of remote sensing orthophoto quantitatively.
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Image segmentation is the technology that separating the image into several characteristic areas and is very important to
image analysis. In this paper, we propose a new segmentation method based on rival penalized controlled competitive
learning (RPCCL) and watershed transform. We apply watershed transform and RPCCL clustering algorithm separately
on input image, and then combine the two results of them. Compared to traditional watershed segmentation, our method
can avoid over-segmentation and obtain better results.
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In this paper, a new approach to objectively assess the performance of image fusion algorithms is proposed. It is based
on the quaternion representation for the structural information of color images. Quaternions are used to encode the pixels
of a color image into a quaternion matrix. Local variance of the luminance layer of color image is taken as the real part
of a quaternion, then the three RGB channels of the color image are encoded into the three imaginary parts of the
quaternion. The angle between the singular value feature vectors of the quaternion matrices corresponding to the source
image and the fused image is used to measure the structural similarity of them. Different weight is given to the source
images by using variance. The experiment results show that the proposed assessment method is consistent with the HVS.
The color information of a color image can be fully used by this method. It can give an accurate assessment result for
each fusion algorithm by using the source images and the fused image.
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In many imaging systems, the detector array is not sufficiently dense to adequately sample the scene with the desired
field of view. In order to enhance the existed image resolution, several approaches to solve this problem have been
investigated previously, such as maximum a posteriori probability (MAP), projection onto convex sets(POCS) etc. Those
algorithms enhance reconstruct high resolution with reduced aliasing, from a sequence of undersampled frames. But
whether POCS, or MAP estimator in space domain, image pixels are rearranged by using lexicographic ordering as a
large matrix in procession. These methods have to solve a large ill-condition equation group, which leads to a big burden
of computation and storage, complexity of algorithm. So they are rarely used in practical application.
In order to solve these problems, a novel reconstruction high resolution(HR) image algorithm based on the standard
displacements of low resolution(LR) images is proposed. Moreover, a set of recursive updating algorithm models is
presented. The results of simulating experiments show that the resolution, the details as well as the definition of the high
resolution image given by using our method are greatly enhanced. At the same time, the running speed of our method is
greatly faster than other super-resolution methods.
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This paper chooses precipitation and temperature data from 106 stations in the Northeast of China from 1951 to 2007.By
using time series analysis, Kriging analysis and other mathematical methods, combined with geographic information
system technology, we analyzed precipitation and temperature change on a time and space of this region during nearly
60 years. The results show that the average temperature in the northeastern region exhibits an increasing tendency during
nearly 60 years. The average temperature has stage characteristics. Temperature fluctuation was greater between 1951
and 1970. The temperature was mainly on the rise between 1971 and 1988 but the change range was relatively small.
Since 1989, there appeared significant warming process and the trend was obvious. On the precipitation change,
precipitation was decreasing tendency on this area and had bigger fluctuation. The period (1951-1970) is rainy period.
The period (1971-1988) is less rain period and annual fluctuation range of precipitation is not big. Since 1989, annual
fluctuation range of precipitation was relatively large. The period since 2000 was obvious less rain period. In the spatial
distribution, the temperature change range was gradually strengthened from the southwest to the northeast between
prophase and middle. Changes of precipitation have different degree decrease in most northeast area except northern
mountain area. The temperature change range was gradually strengthened from the southeast to the northwest between
middle and late. Precipitation changes range in the northern mountain of the area is smaller, while the western and
south-western plain areas have larger precipitation change range.
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In this study, a combined algorithm using the Contourlet transform and morphology is proposed to detect the
significant spatial patterns of ocean eddies. Contourlet transform, which is introduced recent years, has better performs in
representation of geometry lines or curves than the wavelet transform. The source image was decomposed by Contourlet
with several levles, the high-frequency images is divide into eight directions by the directional filter in each level. Then
deal with the high-frequency and low-frequency coefficients separatically, use mathematical morphological method
extracts edges in low-frequency approximate. At last, the two edge images were rebuilt to obtain an integrated and clear
edge image. The Hough transform is than used to extract the characteristic of the eddies. The experimental results show
that this algorithm cabin the priority of the Contourlet and morphological method and is superior to other traditional edge
detection method such as the grads method, the Sobel method, or morphological method alone. The study verified that
the algorithm proposed is an effective way to identify and detect ocean eddies with complex form.
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Super resolution reconstruction is to produce one or a set of high resolution images from a sequence of low resolution
images using the additional information among them. Traditional super resolution reconstruction algorithms are limited
to their assumed data and noise model. The robust reconstruction algorithm which is not sensitive to model error has
always been a hot research. We propose an alternate approach based on p-norm minimization and robust regularization
with bilateral total variation (BTV). This method is robust to errors caused by motion and blur estimation. Hybrid
steepest descent and limited storage quasi-Newton method is used to solve the cost function. Experiments are carried
out in simulated images and ASTER multi-band thermal infrared images, experiment results indicate that the proposed
method removes noises effectively and results in fine detail, sharp edge and rich content.
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Remote sensing image presented as one of the most effective methods to acquire the disaster information in the
Wenchuan earthquake. For its technical advantages such as rapid and flexible takeoff, the Unmanned Aerial Vehicles
(UAV) played an important role in the "5.12" Wenchuan earthquake emergency relief. The UAV remote sensing image
has some special characteristics contrasting with other RS image, so how to process quickly the images is the key issue.
In this paper, a fast method is presented for moisacing the remote sensing images from the UAV without ground control
points. The method grounds on two principles, parallel computing and digital photogrammetry. The experimental results
justify the needs of uncontrolled mosaic images production for the requirements of post-disaster emergency. The mosaic
images without correction by ground control points provide no geographic information, but they can provide panoramic
and macro-information of earthquake-stricken areas. Then the geometric correction technique was employed to correct
the panoramic mosaic images to obtain the high-precise digital orthophoto based on the pre-disaster information such as
topographic maps. By using the object-oriented method for the information extraction and rapid automatic classification
of the UVA remote sensing image can achieve the anticipative goals.
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In recent years, large-sized seaweed, such as ulva lactuca, blooms frequently in coastal water in China, which threatens
marine eco-environment. In order to take effective measures, it is important to make operational surveillance. A case of
large-sized seaweed blooming (i.e. enteromorpha), occurred in June, 2008, in the sea near Qingdao city, is studied.
Seaweed blooming is dynamically monitored using Moderate Resolution Imaging Spectroradiometer (MODIS). After
analyzing imaging spectral characteristics of enteromorpha, MODIS band 1 and 2 are used to create a band ratio
algorithm for detecting and mapping large-sized seaweed blooming. In addition, chlorophyll-α concentration is inversed
based on an empirical model developed using MODIS.
Chlorophyll-α concentration maps are derived using
multitemporal MODIS data, and chlorophyll-α concentration change is analyzed. Results show that the presented
methods are useful to get the dynamic distribution and the growth of large-sized seaweed, and can support contingency
planning.
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Satellite images and field temperature data have been used to derive the winter snow cover change in the northwest
inland regions for the period 1978-2005. Decomposition of the satellite-derived snow depth field yields several
statistically-significant EOFs (modes) and spectrums of variability according to the selection rule. The first three leading
EOF modes account for 63%, 5%, and 4% of the total variance respectively. Spatially, their sensitive regions are
characterized significantly with slope orientation, EOF1 towards northwest, EOF2 towards south and EOF3 towards
southeast. A primary analysis shows the three modes can be explained by the precipitation events induced by the water
vapor conveyed by atmospheric circulation originated from northwest, south and southeast oceans accordingly. As for
the temporal dimension, EOF1 shows evidently different from EOF2 and EOF3, and services as a stable process during
the 27 years. Their temporal processes correlate temperature in a complicated way. On the whole, the temperature
correlates EOF1, EOF2 and EOF3 more significantly, which indicates the impact of climate warming to the snow cover
is, to some extent, acted with circulation originated from different orientations, or as a result of their interactions.
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Synthetic Aperture Radar interferometry (InSAR) is a rapidly developing technique for earth
observation. Differential InSAR (D-InSAR) technique, based on InSAR, is a new method for
earthquake deformation detection and land subsidence monitoring. In this paper, an innovative method
of generation of interferogram for D-InSAR based on contoured correlation interferometry (CCI) is
presented, which may directly generate interferogram with almost no speckle noise or blurring. The
data processing results of the Mani earthquake indicate that D-InSAR CCI method can effectively
reduce or even remove the decorrelation noise, even in the area with serious decorrelation.
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The Spectral Angle Mapper (SAM) algorithm is used widely in hyperspectral data processing, such as classification,
detection, identification, etc. In many cases, however, the classification result of SAM is not satisfied. The aim of this
study is to improve the classification precision of the Spectral Angle Mapper (SAM) algorithm through investigating the
change of similarity between the reference spectra and the selected spectra, evaluated by SAM, in the feature space. The
properties of result calculated by SAM algorithm are exploited in the feature space whose dimensionality is equal to the
number of bands. A new method, which represses the impact caused by the additive factor in the feature space, is
proposed in this paper for its improvement on performance versus traditional SAM algorithm. The spectral
discriminability of the new algorithm is greatly improved by reducing the additive factor in the feature space
appropriately. In order to demonstrate its enhancement, a comparative study is conducted between the new algorithm and
the SAM. The comparative results prove that the new approach can control the errors effectively and improve the
precision and reliability of classification significantly. The new algorithm is implemented in IDL7.0 and tested in ENVI,
using 1995 Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data from Cuprite, Nevada, USA.
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This paper presents a new blending approach: Using meso-scale Numerical Weather Prediction (NWP) products as
environment field, coordinating with weather radar information, blending radar data and NWP model products together,
and finally being applied to short-range forecast and nowcasting. Considering the fact that the weight of radar
extrapolation and NWP model products should be adjusted because they will change with time, three solutions are
offered to calculate NWP weight to blend radar extrapolation and NWP model products in a certain area. At last, RMSF
method is used to verify and examine the example. After qualitative comparison with figures, the results showed:
blending with equal weights and blending with sin2(at+b) as NWP weight improved radar extrapolation and NWP results.
A new effective way has been discussed preliminarily. Hoping it is of reference value to short-range forecast and
nowcasting in further research.
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Performance of the selected algorithm is crucial for hyperspectral target detection. However, it is sure that there is no
algorithm that is appropriate for all hyperspectral data or applications. Result of detection can be affected by many
factors, including spectral feature of targets and backgrounds, characteristic of spectrometer and pre-processing method.
Thus to improve practicability of hyperspectral target detection, studies should not be focused solely on the algorithms,
but also be extended to discussion of above affecting factors. In this paper, hyperspectral imagery measurements and
data processing are studied. Six aspects including paints, spectral response, imaging spectrometer mode, image noise and
dimension reduction are discussed. Typical abnormity and matching algorithm are applied on images simulated with
different factors. The influences of these factors on target detection are analyzed. At last, this research provides a
strategy for precision control of target detection in hyperspectral imagery. Researches in this paper can be of great help
for algorithm development and algorithm selection in diversified hyperspectral data and applications.
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To overcome the disadvantages of single non-metric camera with small format and short baseline, a wide-angle camera
system is developed with the combination of four digital cameras
(UAV-LAC) to meet low altitude photogrmmetric for
acquiring both facades and rooftops high resolution texture of 3D city model. A relative self-calibration method based on
tie points in the overlapping areas of each two sub images is used to make compensation for the deformed errors due to
the light and simple constructed mechanical frame. AAT is used to rapidly retrieve pose parameters of mosaic image and
original inclined images. After that, space forward intersection algorithm is used to gradually improve the building
model as well as matching each space edge of building. Next, geometrical rectification is considered for textures and the
best textures for wall and roof are selected by taking into account occlusion, image resolution, surface normal
orientation, and coherence with neighboring triangles. Finally, by incorporating friendly necessary human interaction
into texture reconstruction algorithm, an semiautomatic system is designed to reconstruct texture from UAV-LAC.
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Shallow water depth extraction by remote sensing is an important research. Optical remote sensing can provide an
alternative means for obtaining bathymetric data in areas where a traditional hydrographic survey may be difficult to
obtain. IKONOS imagery can perform an important function in shallow water depth extraction because of its ability to
provide data within three unique portions of the visible spectrum as well as a high spatial resolution of roughly four
meters. But experiments indicated that, the bathymetric precision of high-resolution imagery is much lower than that of
mid-resolution imagery such as TM imagery. In this paper, the affect factors of bathymetric precision of high-resolution
imagery are presented. Moreover, on the basis of the conventional multi-band linear regression model , we develop an
improved model by introducing a series of techniques including data processing by group averaging, image smooth,
piece wise linear regression, data normalization, etc.. The improved model is more reasonable and accurate and suitable
for high-resolution imagery. Using this improved mode, the shallow underwater topography of Dong-Sha Islands and
nearby sea area is detected by IKONOS image. The results have preferable precision.
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The visual effect is an important fact in the coding algorithm. So the saliency of visual attention(SVA) can be used to
determine the region of interest(ROI) in the ROI image coding. A novel SVA based ROI(SVA-ROI) image coding
scheme is presented for the reconnaissance satellite systems. As the SVA of the original image and reconstructed image
are usually the same, the same ROI can be automatically determined in the encoder and decoder with the SVA. Then the
ROI side information is no need to be transmitted and the compression efficiency can be improved. Experimental results
have demonstrated that SVA-ROI has better visual effect than the similar algorithms, which will be suitable for the
reconnaissance satellite systems.
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Bamboo is an important forest resource at sub-tropical regions in China, which continuous expansion has taken place in
China during the last 20 years. Monitoring its distribution has important significance. It provide a possibility that we can
extract accurate information among vegetation types as result of detailed texture features, patterns, optical information
can be obtained from IKONOS image. In this paper, Anji Country in Zhejiang province was selected, deriving bamboo
information from IKONOS image by using Iterative Self-Organizing Data Analysis Technique(ISODATA) classify
method, Decision Tree method based on NDVI and texture and Object-oriented classification algorithm based on texture
and spectral bands were discussed. The results showed that Decision Tree method based on NDVI and texture
demonstrated high accuracy (Kappa=0.7428). Additional, Object-oriented classification algorithm based on texture and
spectral bands suggested the highest user's accuracy 93% and producer's 78% at deriving bamboo information, which can
be adapted to deriving bamboo information from IKONOS image at subtropical regions in China.
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The remote sensing method has many advantages such as large coverage, multi-temporal dynamic monitoring and
historical backward monitoring. In this paper, remote sensing images from Landsat-5, Landsat-7 and CBERS-1 satellites
are acquired for extracting shoreline, reclamation, tidal flat and current path information. The characteristics of
reclamation and inter-tidal flat are analyzed. Then, the spatiotemporal evolvement of inter-tidal flat and current path
under the influence of reclamation projects is presented. The work shows that the remote sensing technology is a
valuable method for multi-temporal dynamic monitoring and historical backward monitoring for estuarine tidal flat, and
that inter-tidal flat evolvement and current path is influenced by reclamation projects mainly.
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Typhoon cloud image retrieval is very important for typhoon research and forecast. In this paper, we designed a multifeature
typhoon cloud retrieval system. Using this system, we investigated eight Content-based Image Retrieval (CBIR)
methods, including histogram-based, texture-based, shape-based and entropy-based retrieval methods. The performance
of these methods was tested by three experiments from different aspects. They are paradigm retrieval experiment,
random statistical validity experiment and random statistical efficiency experiment. The experimental results indicate
that the validity and effectiveness of entropy-based retrieval method is the best in all the methods. And some methods
(like HU moments-based image retrieval method) are not suitable to the typhoon cloud images retrieval.
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Currently, how to effectively utilize assimilation technique to retrieve biophysical parameters from time series remote
sensing dada has attracted special concern. The assimilation technique is based on a reasonable consideration of the
dynamical change rules of biophysical parameters and the time series observational quantities, thereby improving the
quality of the retrieved profiles. In this paper, a variational assimilation procedure for retrieving leaf area index from
time seires remote sensing data is investigated. The procedure is based on the formulation of an objective function, and
SCE-UA optimization method is used to estimate LAI from the MODIS reflectance data with a higher quality in a given
time window. A preliminary analysis using MODIS surface reflectance data at some sites was performed to validate this
method. And the results show that the algorithm is able to produce temporally continuous LAI product efficiently, and
the accuracy of the retrieved LAI has been significantly improved over the MODIS LAI product compared to the field
measured LAI data.
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We propose a joint source and channel remote sensing image compression system for image transmission over Binary
Symmetric Channels (BSC). As an effective wavelet-based compression scheme, Set Partitioned Embedded Block Coder
(SPECK) is quite fragile against bit errors in noisy channels. To avoid the failure caused by the loss of synchronization
and the error propagation, we improve the error resilience of SPECK with an acceptable degradation of quality. The
novel packets division permits to continue reconstructing image when uncorrectable errors occur. The system makes full
use of the bit-stream and the simulations show the scheme is better than an Equal Error Protection scheme (EEP) and a
Unequal Error Protection scheme (UEP).
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The surface environment and the thermal infrared information of remote sensing have been widely used to study urban
climate. In this paper, the Landsat Thematic Mapper (TM) data acquired in 2008 were applied to study the relationship
between urban surface temperature and surface characteristics within the Beijing 5th ring road area of China. The thermal
band data of TM combined with classification-based surface emissivity were utilized to estimate land surface
temperature (LST). Meanwhile, surface characteristics parameters, such as the Normalized Difference Vegetation Index
(NDVI), the Modified Normalized Difference Water Index (MNDWI), the Normalized Difference Building Index (NDBI)
and the Normalized Difference Bareness Index (NDBaI) were calculated according to related arithmetic respectively.
The quantitative relationship between LST and NDVI, MNDWI, NDBI and NDBaI were investigated according to urban
main land use/cover types (water body, vegetation and built-up surfaces). The results showed there were negative
correlations between LST and NDVI, MNDWI for vegetation and built-up land use/cover types, positive correlations
between LST and NDBI, NDBaI for vegetation and built-up land use/cover types. In general, in the area 5th ring road of
Beijing the distribution of NDVI, MNDWI and NDBI directly defined the distribution of LST. For built-up land
use/cover type, the NDVI was small, However, NDBI and LST were high. While in the area with more water and
vegetation, the NDVI and MNDWI were high and LST was small. There were obvious correlation between LST and
urban surface characteristics.
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To some extent, the multi-level dynamics of an atmosphere system implies temporal structures in time-varying climate
data. Here the multi-period issue of temperature data is studied. Since the scale parameter of wavelets is not easily
understandable, the relationship between time period and time scale is formulated in Morelet wavelet. Unlike overall
multi-period and -frequency information in Fourier analysis, wavelets analysis provides us with local multi-period
information. At Changchun meteorological station, our experimental dataset are daily temperature measurements from
1951 to 2005. After a wavelet transform of climate dataset, modes and real parts of wavelets coefficients are drawn for
visually exploring local multi-period information. In particular, it is seen that the time periods of 1 year, 3 to 4 years are
globally apparent, and the time period of 8 to 12 years is locally apparent. For the temperature, there is an overall trend
of colder and warmer interchanging time periods, i.e., a colder period before the middle 1980s and a warmer period from
the middle 1980s to present. These two time periods are further divided into four cold periods and three warm periods
respectively. In a large time period, 1987 is the year of abrupt temperature change. In a middle time period, 1970 is the
year of abrupt temperature change. In the time period of year, there exist specific years of abrupt temperature change. In
our framework of spatiotemporal data mining, these local multiple periods are used for creating multi-level spatiotemporal
meteorological association rules. It is proved that the Morelet wavelet is feasible for exploring temporal
structures in climate data.
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The specification of OGC (Open Geospatial Consortium) Web Processing Service (WPS)[1] puts forward some uniform
interfaces to manage, browse, query and perform kinds of Geographic disposal. At present, most of the WPS services
implementing the interfaces can be called only based on HTTP GET/POST requests. This situation makes it difficult for
us to vastly composite, integrate and reuse these atomic services, through Business Process Execution Language
(BPEL)[2] that has been very mature. This paper brings forward a method to better solve the problem, and, at the same
time, a composite process is carried out by chaining the atomic services of WPS to implement the complex Geographic
data disposal, which proves the effectiveness of the method.
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In photogrammetry data processing, the uncertainties in the observations will lead to model error, which is the difference
between the model and the reality. This model error may cause wrong results if the traditional parametric model is used.
In order to solve this problem, Semi-parametric model, based on parametric model, is implemented in this article. Semiparametric
model introduces a non-parametric component to describe the uncertainties in the observation data and their
influences. Both parametric and non-parametric unknowns are solved by penalized least squares. Testing results indicate,
that in the existence of observation uncertainties, Semi-parametric model can effectively isolate model error, thereby
making it a better approach than parametric model.
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This paper addresses the problem of remote sensing image classification based on the semantic context using
Discriminative Random Field (DRF) model. The DRF model is used to capture the highly complicated spatial
interactions and contextual information in remote sensing images. The DRF labels different image regions by using
neighborhood spatial interactions of the labels as well as the observed data. Based on the DRF model, a graph-based
inference algorithm--Belief Propagation (BP), is employed to obtain the optimal classification result. This inference
algorithm is efficient in the sense that it produces highly accurate results in practice compared to other traditional
inference algorithms.
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Solar storms in the ionosphere have a great impact on human's life. It's of great significance to find an effective way for
an accurate prediction of solar storms. In this paper, we present a method based on GUVI FUV day-glow imaging data to
derive O/N2, an environmental parameter used to forecast Space Weather. In the retrieval, we selected two channels of
the FUV wavelengths, OI135.6nm and LBH2. In accordance with the linear relationship between O/N2 and 135.6/LBH,
we proposed 135.6/LBH to describe O/N2. With the method described in this paper, the data of a 4-day solar storm,
October 1 to 4, 2002, have been processed. Subsequently, the obtained O/N2 maps were in good agreement with previous
results. It demonstrated the retrieval process we put up is efficient.
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A method of feature validity analysis is proposed in this research. More than 100 kinds of features which are commonly
used in the remote sensing image analysis have been selected. In this process, we choose level set and Otsu segmentation
methods to extract the target and use manually segmented target images as templates, based on the method, we can make
a evaluation of these features validity especially the stability in multi-resolution.
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This paper proposed an unsupervised change detection method for water body extraction and change detection with
multi-temporal SAR images. Firstly, two optimal thresholds are estimated according to the strategy of maximum mutual
information, in which computation efficiency is largely improved based on integral image. Secondly, water body
extraction is done simultaneously in both input images by optimal thresholds. Finally, by fusing of two segmented
results, change detection can be achieved. Experimental results demonstrate the effectiveness of the proposed approach.
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aIn this paper, band-combining operation is applied to extract water body area of three different period remote sensing
pictures. Based on the Beijing wetland management classification system of wetlands and wetland patches census data,
through the superposition of space under the counter-analysis and recursive speech, build a VBA classification, different
stages of the wetlands water are separated automatically in order for the organic connection and unity of data from
wetland administration section and remote sensing data. The results show that: (1) Decision tree is a good way to get the
whole water information. All the information of water can be extracted by tm2 + tm3> tm4 + tm5, but there are still
some mixed information. Towns and clouds can be removed when tm5 and tm7 less than a specific threshold, and
shadow of the mountain can also be removed well when tm3-tm4 are greater than a specific threshold. (2) The urban
wetlands can be obtained rapidly with the secondary development of VBA functions in GIS. (3) This classification
method has high accuracy, the overall classification accuracy is 91.8%, kappa statistics is 0.88, and this method avoid
post-processing work, is very time-sensitive.
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In order to analyze the changes of underlay features in the urbanization process and their impact on characteristics of
spatial distribution of LST in Beijing-Tianjin-Tangshan (Jingjintang) metropolitan region, MODIS LST Product and
SPOT VGT NDVI Product are collected and their statistical features are calculated, then LST, Land cover/use (LULC)
and their relationship are studied in detail. The main conclusions drawn from this research are as following: (1) there is
different LST in different land surface with different land cover type. LST in urban and built-up region is maximum,
LST in water region is minimum. And there is a negative correlation between NDVI and LST. The higher NDVI value
is, the lower LST value is. (2) In Jingjintang region, there is higher NDVI and lower LST in 2006 than 2002, about
38.56% and 18.10% in turn. About in the single city, there are different change values. The change value of LST presents
Beijing > Tangshan > Tianjin, (3) Comparison 2006 to 2002, the surface of Jingjintang region is dominated by class with
both NDVI and LST increase and the percentage is 41.79%. The percentage of the class with NDVI increase and LST
decrease is about 29.23%, 29.9.% and 39.40% in Jingjintang region, Beijing and Tianjin. And that with NDVI decrease
and LST increase is about 20.57%, 14.75% and 12.12% in Jingjintang region, Beijing and Tianjin. Tangshan urban
region is dominated by the class with NDVI decrease and LST increase, up to 35.54%. On the other hand, the percentage
of NDVI increase and LST increase is about 26.36%. The different NDVI and LST change trend shown in different
regions may result in their different urbanization level.
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Large opencast coal mine area is a complex region which consists of mining area, grassland, farmland, roads, residents
and other landscapes, together with the typical characteristics of desertification, agro-pastoral transitional zone, mineral
development area and other ecologically fragile areas. As a man-caused disturbance, mining plays an important role in
desertification development in this area. The quantitative extraction of desertification integrating multi-source remote
sensing data in large opencast coal mine area was studied in this paper. First, the remote sensing data from SPOT 5 and
TM were fused to one image based on IHS transformation and Wavelet analysis, then the BP neural network algorithm
were used to fusion image to get desertification classification information. The Global Positioning System (GPS)
technique was also used to perform verification during the data process. The results of our studies indicate that the severe
desertification is always distributing in shape of triangle around the mining land, which has much spatial correlation with
the mining land. So the desertification management should be carried out in mining land, the neighbor region of the
mining land should not be neglected.
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Using Geographic Information System (GIS) and evaluation model integration technology of soil heavy metal pollution
to survey, sample and analyze of the eight kinds of heavy metals in the black soil region (Dehui) of Jilin province in
northeast of China. Following the national soil environmental quality standard, the single pollution index was used to
elevate the pollution degree of single element, and the result of this evaluation was the Comprehensive pollution index.
Based the spatial distributing rules and characteristics of heavy metals content of soil in study region, outputted the
evaluation chart of soil heavy metal pollution of both the single and the Comprehensive pollution, and analyzed the
status of the soil heavy metal pollution. As the data indicated, the quality of the soil in study region was nice, there was
no large Comprehensive heavy metal pollution region. However, it was worth to attention that the element Ni had a great
distributing bound and the index of pollution was high.
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Volcanic activity can present unpredictable disasters to city populations living within regions and for people traveling in
plane that intersect with ash-laden eruption clouds. Methods of monitoring volcanic activity include searching for
variations in the thermal anomaly, clouds resource and subsidence deformation from active volcano. Over any active
volcanoes, low spatial resolution satellite image are used to identify changes in eruptive activity, but are of insufficient
spatial resolution to map active volcanic features. The Landsat data can be used to identify the thermal characteristics of
a series of lava flows at Fuego volcano and Pacaya volcano, Guatemala. We use Landsat TM/ETM+ 7, 5, 4 (displayed in
red, green, and blue, respectively) false-color composite of the research region, acquired on 18 December 1989 and 23
January 2000 to indicate the volcano image features which appear halo structure with blue red and yellow. The
interpretation flag is obvious which indicate the difference temperature of volcano crater. Spatially varying haze emitted
by volcano activity is identified and removed based on Improved Haze Optimized Transform (HOT) which is a robust
haze assessing method. With improved spatial resolution in the thermal IR, we are able to map the bifurcation and
braiding of underground lava tubes. With higher spatial resolution panchromatic data, we are able to map lava flow
fields, trace very high temperature lava channels, and identify an accurate feature associated with a collapsed crater floor.
At both Fuego and Pacaya, we are able to use the thermal data to estimate temperature. We can monitor the dynamic
change of the two volcanoes using two difference date Landsat data.
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Carbon monoxide is an important atmospheric pollutant whose emissions and atmospheric concentrations need to be
monitored. This paper presents the spatio-temporal gradients of carbon monoxide in China based on the vertical columns
of carbon monoxide measured by the SCIAMACHY sensor on board ENVISAT during 2003-2005. The annual average
of carbon monoxide vertical columns is up to 2.3×1018molecule•cm-2 more than the background 1.6×1018molecule•cm-2.
The seasonal variation of carbon monoxide vertical columns is obvious. The peak centers of monthly averaged carbon
monoxide occurred in winter and spring, whereas the troughs in summer. The high concentrations of carbon monoxide
are distributed on the Yangtze Delta, around Sichuan Basin, around Beijing regions and the Pearl Delta. The carbon
monoxide concentration has a strong correlation with
government-generated provincial-level statistical data on
environment and energy. The regional pollution as well as biomass burning plays an important role for carbon monoxide
levels over China and that SCIAMACHY is a promising tool for comprehensive understanding of carbon monoxide
gradients and emissions.
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SPECK has been found to be competitive in compression of the remote sensing images with abundant texture, while the
visual importance of DWT LL sub-band has not been utilized in the SPECK. To improve the compression capability of
the SPECK further, this paper presents the LFP-SPECK (Low Frequency Prior SPECK) algorithm. By lifting the bit
planes of low frequency sub-band coefficients LFP-SPECK algorithm encodes low frequency sub-band firstly. The
double LSP (List of Significant Pixels) lists are adopted here to avoid increasing bits by lifting bit planes. In addition, the
optimal single-value linear prediction method is used to decrease the redundancy of the LL sub band. The experimental
results with remote sensing and aerial images show that LFP-SPECK algorithm is better than SPECK and the LSPECK
(Lifting SEPCK) algorithms.
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The evaluation of performances of fusion methods is a key problem in remote sensing image fusion. In this paper, four
representative fusion methods, PCA fusion, WT fusion, CT fusion and TLS-GIF-WC, are adopted to fuse two sets of
ALI images for comparison. The fusion products are applied to two remote sensing applications, vegetation index
extraction and image classification. The normalized difference vegetation index (NDVI), vegetation coverage and
classification accuracy indices are adopted to compare the fusion products. Experiments show that the GIF fusion
products are more adaptive for vegetation application, since the NDVI and vegetation coverage extracted from the fusion
product are consistent with that extracted from the initial image, and the ARSIS concept fusion and TLS-GIF-WC
products are more adaptive for image classification, because of the higher classification accuracy.
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When facing complex requirements of city development, ever-growing spatial data, rapid development of geographical
business and increasing business complexity, collaboration between multiple users and departments is needed urgently,
however conventional GIS software (such as Client/Server model or Browser/Server model) are not support this well.
Collaborative application is one of the good resolutions. Collaborative application has four main problems to resolve:
consistency and co-edit conflict, real-time responsiveness, unconstrained operation, spatial data recoverability. In paper,
application model called AMCM is put forward based on agent and multi-level cache. AMCM can be used in mixed
network structure and supports distributed collaborative. Agent is an autonomous, interactive, initiative and reactive
computing entity in a distributed environment. Agent has been used in many fields such as compute science and
automation. Agent brings new methods for cooperation and the access for spatial data. Multi-level cache is a part of full
data. It reduces the network load and improves the access and handle of spatial data, especially, in editing the spatial
data. With agent technology, we make full use of its characteristics of intelligent for managing the cache and cooperative
editing that brings a new method for distributed cooperation and improves the efficiency.
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The distribution and allocation of different land cover classes is related with resource exploitations, environmental
pollution controlment and human habitat environment quality. In this paper, the multi-source data including high
resolution RS imagery-FORMOSAT-2 image and digital topographic maps are applied to acquire the information of
urban land cover by taking Chongming as a case study. Firstly, the overall framework is proposed to apply multi-source
data to extract and classify urban land covers. Then, some classes of land cover are extracted and the high resolution RS
imagery is classified based on C5.0 decision tree classifier. In the feature library of different urban land covers
established, there are three features: spectral feature, texture feature, and shape information. Spectral and texture features
are acquired from the RS imagery, and shape information is computed from digital vector maps using ArcGIS. Based on
multi-feature, the classification model via C5.0 decision tree is constructed to realize the urban land cover classification
and extract different land cover classes. Finally, classification accuracy and results are compared between this method
and other conventional classification methods. This method proves to improve the classification accuracy more
effectively.
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Multi-sensor image fusion has its effective utilization for surveillance and navigation. It provides a way to merge multisensor
imagery by combining the outputs of different imaging sensors. In this paper, we utilize a variational approach to
fuse images from different sensors, in order to enhance visualization for surveillance. Energy functional is established in
a contrast vector field and a successive over-relaxation method is utilized to solve a Poisson equation. Experimental
results show that the variational approach is robust and effective, regardless of time-consuming.
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The spatial heterogeneities of hydrological parameters in watersheds with limited extents should be accounted by the
distributed hydrological model. Dongting Lake is selected as the study area and divided into 19759 hydrological
response units based on DEM according to the concept of drainage density. Each unit has one land-use type and one soil
type. The hydrological response units are utilized as the minimum units in simulations of hydrological processes and a
parameter database of the distributed hydrological model is designed under the support of GIS. The parameters are
managed with layers in the database. The structure of the database is helpful for organizing and updating the parameters.
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The advance of image processing makes knowledge-based automatic image interpretation much more realistic than ever.
In the domain of remote sensing image processing, the introduction of knowledge enhances the confidence of
recognition of typical ground objects. There are mainly two approaches to employ knowledge: the first one is scattering
knowledge in concrete program and relevant knowledge of ground objects are fixed by programming; the second is
systematically storing knowledge in knowledge base to offer a unified instruction for each object recognition procedure.
In this paper, a knowledge-based framework for ground objects recognition in remote sensing image is proposed. This
framework takes the second means for using knowledge with a hierarchical architecture. The recognition of typical
airport demonstrated the feasibility of the proposed framework.
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Based on digital elevation model (DEM), the distributed models for calculating possible sunshine (PS) over rugged
terrains (RT) are established and this model considers the influence of slope, aspect, and terrain inter-shielding. The
spatial distribution of PS with 100m×100m over RT in Guiyang city is calculated by this model. The results show that
the influences of slope, aspect and the terrain inter-shielding on PS are very big and it is greater than the effect of latitude.
The spatial distribution of PS over RT in Guiyang city has apparent terrain feature. The spatial difference of PS over RT
is big. The values of annual PS over RT in Guiyang city are 3233~4368 hours, the difference is large in different regions.
The smaller values lie in shady slope of the mountain. The bigger values lie in sunny slope of the mountain. The values
of PS over RT in the Guiyang city are 154~322 hours in January. The values of PS over RT in Guiyang city are 411~421
hours in July.
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In remote sensed images, mixed pixels will always be present. Sub-pixel mapping is a technique to farther make
sure the spatial distribution of all classes. The present sub-pixel mapping techniques always have a limit to the accuracy
since they are based only on the soft-classified proportion data at the pixel level. In fact, supplementary information at
the sub-pixel level can be used to enhance precision. In this paper, a proposed method aims to use fused imagery as
supplementary information sources for the traditional sub-pixel mapping model development. The fused image with high
resolution is obtained using a Gram-Schmidt spectral sharpening method, then new abundance images can replace the
original data and provide more details through the Linear Mixing Model (LMM) and Fully Constrained Least Squares
(FCLS) method, finally the prepared data are incorporated in a Fuzzy ARTMAP neural network. The completed
algorithm is tested on a synthetic SPOT5 MS image, PAN image should be taken as a reference image. The result
suggested that fine spatial resolution fused imagery can be used as a supplementary data for sub-pixel mapping, and it
can get better performance than directly ANN method.
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This paper presents a registration method which based on straight lines primitive. Firstly, 2D straight lines are extracted
from aerial images using Canny operator and straight line fitting. In the similar way, 3D straight lines are extracted from
LiDAR range images which derive from laser scanning point cloud. Secondly, 3D straight lines are projected to aerial
images using collinearity equations and Position and Orientation System (POS) data. Then the corresponding lines are
determined by straight line error. At last, each image's new exterior orientation elements are calculated by generalized
point (straight line) photogrammetry.
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With the development of the OpenGIS WFS (Web Feature Service) Specification by OGC (Open GIS Consortium), more
and more WFS servers appear on the internet offering geospatial information. However, general users have no
acquaintance with these servers, and the servers usually supply data encoding in GML (Geographic Mark Language)
which cannot be comprehended vividly. Therefore, in this paper, we propose a spatial information search and display
System on OpenGIS WFS. This system is capable of providing a WFS server list containing the data of the place that the
users requested, retrieving the capabilities of the service chosen by the users and displaying the service data in vector
graphics. The system architecture, working principles, and detailed function of each component are introduced. With this
system, a practice web search engine on OpenGIS WFS can be constructed on the foundational idea of the system.
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The remote-sensed images may be degraded by some factors during their obtaining. It decreases the quality of the
images and becomes an obstacle of the image recognition. So it's very necessary to restore the degraded image. At
present, most of the image restoration algorithms are depended on the priori knowledge or a given physical model of the
image degeneration. The paper presents a new algorithm for remote-sensed image restoration based on gene expression
programming (GEP). The paper needs a reference image at first; then applies the GEP to mine the math function
between reference image and degraded image; at last, restores the degraded image with the math function. The
experiment results demonstrate that the method is effective and practical.
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The main purpose of the algorithm in this paper is to extract geometry information (mainly includes the plane function,
the outlines and the corners of the building surfaces) from the point cloud. The main process includes: filter and sort the
point cloud, get fitting lines in each column and merge the fitting lines, get fitting faces from the fitting lines and merge
the fitting faces, extract the outlines and corners of the merged faces. The advantage of the algorithm includes: A face's
adjacent faces can be got, the disturbing points can be automatically removed and the computation amount is relatively
small. The algorithm is particularly suit for the point cloud got by vehicle-borne laser scan.
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Water is a key variable in describing the water and energy exchanges between the land surface and atmosphere interfaces.
In this paper a classifier is presented, which is based on integration of both active and passive remote sensing data and
the Maximum Likelihood classification for inversion of soil moisture and this method is tested in Heihe river basin, a
semi-arid area in the north-west of china. In the algorithm the wavelet transform and IHS are combined to integrate TM3,
TM4, TM5 and ASAR data. The method of maximum distance substitution in local region is adopted as the fusion rule
for prominent expression of the detailed information in the fusion image, as well as the spectral information of TM can
be retained. Then the new R, G, B components in the fusion image and the TM6 is taken as the input to the Maximum
Likelihood classification, and the output corresponds to five different categories according to different grades of soil
moisture. The field measurements are carried out for validation of the method. The results show that the accuracy of
completely correct classification is 66.3%, and if the discrepancy within one grade was considered to be acceptable, the
precision is as high as 92.6%. Therefore the classifier can effectively be used to reflect the distribution of soil moisture in
the study area.
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By introducing the object cloud into topological space, the spatial relationships between fuzzy objects transform to cloud
relationships in cloud space. According to cloud theory, all the spatial objects can be represented by three types object
cloud: point-cloud, line-cloud and area-cloud. So the 9-intersection model of spatial topological relations proposed by
Egenhofer can be extended by using the new definition of object cloud. The relationship between object clouds is
flexible relationship. Different from the crisp relationship model, 9IM, the flexible relationship model by object cloud
can be simplified to 4-intersection cloud model(4ICM), including to equal, contain, intersect and disjoint. The cloud
operation and virtue cloud can be introduced to representing the fuzzy and uncertain topological relations. The method
makes spatial data model enable to model the spatial phenomena with fuzziness and uncertainties, and enriches the cloud theory.
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The technology of quickly generating city image mosaic is widely applied in urban planning, evaluating natural disasters
and meeting city's emergency service. This paper utilizes existing 1:2000 orthophoto and 1:500 digital line graph (DLG)
to get control information, and calculate parameters of image mosaic by image matching and aerotriangulation. At last
quick and seamless auto-mosaic is implemented based on Thiessen polygon. Test results prove that our approach can
quickly obtain large mosaic images, which satisfies the need of many society applications.
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In traditional IHS transformation, the panchromatic image directly replaces the intensity component, spatial information
of the panchromatic image is reserved. But it may cause severe spectral distortion at the same time. Enlightened by
correlation coefficient of two images and its physical meaning, a novel IHS transformation image fusion algorithm is
proposed. It's called local correlation coefficient weighted IHS transformation image fusion algorithm (LCCW-IHS).
The weighted parameter is determined by the local correlation coefficient between the high-resolution panchromatic
image and multi-spectral image's intensity component. Then the two images are fused and the new intensity component
is generated. Finally the fusion image is obtained by inverse IHS transformation. This method furthest synthesized the
region characteristics in the original images to be fused. Both the spectral characteristics of multi-spectral image and the
high- resolution features of the panchromatic image are maintained. And the texture details are also enhanced. The
experimental results of multi-spectral image fusion, analyzed by both subjective and objective evaluations, show the
proposed algorithm is effective for image fusion.
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Image registration is an important step of many practical problems, such as image fusion, image analysis and image
inlaying. This paper proposes and implements an automatic image registration algorithm with high precision based on
character points as well as its corresponding parallel algorithm. The algorithm applies Forstner arithmetic operator to
pick up character points and for the first time uses local normalized mutual information to search their matching points.
The normalized mutual information is computed using highly precise Parzen window method. Then single-point least
square method is employed to search the matching points precisely, which are used together with the character points to
compute the transformation parameters. Then the algorithm uses quadratic polynomial transformation to register the
images. Based on the analysis of performance of the serial algorithm, the paper proposes and implements its
corresponding parallel algorithm. The algorithm parallelizes each step according to its characteristic and gives the
strategy of data distribution. The experimental results show that the parallel algorithm gets high efficiency and thus has
good scalability and applicability.
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Cases of ship-bridge collision accidents are large problems in many countries. Bridge markings are crucial factors of
such problems. However, there is lack of adequate and scientific quantitative analysis and effective setting and
evaluation methods in bridge markings setting. The popular methods are still based on experience and afterwards
adjustment. Thus, this paper puts forward a resolution to set and evaluate bridge markings based on 3DGIS and VR, for
aiding navigation safety and securing bridge self-security. A new framework of bridge markings setting and simulation
system based on 3DGIS and VR is proposed. Some key techniques and algorithms including 3D environment simulation,
dynamic effects, and simulation, setting and efficiency evaluation of bridge markings are discussed in detail. Based on
the above algorithms and strategies, a Bridge Markings Setting and Simulation System based on 3DGIS and VR was
developed and applied in Guangdong Marine Safety Administration Bureau.
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Urban land use change is composed of a series of distinctive mutual transformation process, which has a dominant trend
to transfer from non-urban construction land to urban construction land. However, the land use transition is not a direct
change process from a certain land-use type to another one in a narrow area, but has a gradual process range between any
two land use types in a wide region. In this paper, a hybrid model for analyzing urban land use change based on fuzzy
reasoning and cellular automata is proposed to simulate the change process of land use type in the transition areas of
urban and rural area. Then, four transition rules are discussed in detail based on the feature of land conversion behaviour
in the contiguity areas of urban and rural area. An example of application research is experimented in Hankou Town
through remote sensing imagines in 1993, 1998 and 2003. The results suggest that the first transition rule is more
accurate than other three rules in the whole, by which the transition probability depends on by the edge pixels from 1993
to 1998. But different types of land use have own most compatible transition rule among those four rules.
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Land structure and amount directly influence urban development, since it is an elementary resource for various activities
in urban systems. However, land use zoning in urban system is often conducted from the view of economic and social
benefits, not considering ecological benefit. Taking Nanjing city as the study area, the present paper studied land cover
constitution of different land use zoning and constructed the quantitative relationship between urban ecological
parameters of land surface temperature (LST) and land surface dryness (LSD) and land cover constitution. Land cover
information was acquired from IKONOS data based on a decision tree method, LST was retrieved from the thermal band
of Landsat ETM+ data using mono-window algorithm, and LSD was calculated from the LST/NDVI space. Analysis
results showed that land cover constitutions within different land use zonings have great variations, and the relationships
between ecological parameters and land cover constitution also showed a close correlation; the percent vegetated area
had strong negative relationship with LST and LSD, while the percent impervious surface showed obvious positive
relationship with LST and LSD. These conclusions should be considered in urban ecological environment management.
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Systematic mapping and monitoring of wetland landscape are of fundamental importance for wetland development and
management. To accurately classify wetland in Yancheng coastal wetland, ground investigation was conducted in 2006.
Integrated with ground investigation, the wetland was classified into 8 categories such as Spartina alterniflora Loisel,
Farm land, Phragmites Australis, Artemisia halodendron Turcz, Bare beach, Salt field, Fish & shrimp pond, and Sea
water. A total of three decision trees were successfully produced. The first represented broad divisions of vegetation (in
fact, at this stage, it just can be called vegetated cover like) and non-vegetation, and the second two represented more
detailed vegetation classes and non-vegetation classes. To construct the decision trees, NDVI and principal component
analysis were used as the evaluation factors. The thresholds were built combining with ground investigation and spectral
property. Firstly, almost all kinds of vegetable were divided out of non-vegetation by NDVI. Secondly, the different
species of vegetation were distinguished and some vegetated cover like was eliminated out of vegetation. Phragmites
Australis belt, Artemisia halodendron Turcz belt, Spartina alterniflora Loisel belt and bare beach belt were distributed
regularly from land to sea.
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This paper aims at bridging the gap between the academic research and practical application in water environment
monitoring by remote sensing. It mainly focuses on how to rapidly construct the Inland and coastal Water Environment
Remote Sensing Monitoring System (IWERSMS) in a software perspective. In this paper, the remote sensed data
processing framework, dataflow and product levels are designed based on the retrieval algorithms of water quality
parameters. The prototype is four-tier architecture and modules are designed elaborately. The paper subsequently
analyzes the strategy and key technology of conglutinating hybrid components, adopting semantic metafiles and tiling
image during rapid construction of prototype. Finally, the paper introduces the successful application to 2008 Qingdao
enteromorpha prolifra disaster emergency monitoring in Olympics Sailing Match fields. The solution can also fit other
domains in remote sensing and especially it provides a clue for researchers who are in an attempt to establish a prototype
to apply research fruits to practical applications.
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Automatic 3-D building reconstruction is the key technology of "digital city" construction, which can be widely used in
urban planning and management. In this paper, we firstly analyze the disadvantages in traditional automatic building
reconstruction methods, and then according to characteristics of complex buildings, which is multi-storey and non-flattopped,
a new automatic building reconstruction method is proposed, which can solve the complex building
reconstruction problem effectively and conveniently. The reconstruction experiments show that the proposed method has
excellent universality, besides a small calculating amount compared with traditional methods.
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The paper explorers the application of ANFIS (Adaptive Network-based Fuzzy Inference System) in the extraction of
remote sensing information of wetland, which integrates the advantages of fuzzy inference and neural network. Firstly,
the paper discusses characteristics, principles and process of the method. Secondly, Taking the wetland of Yellow River
Delta in KenLi County as the experimental area, it analysis the extraction of remote sensing information of wetland
based on ANFIS. Finally, it compares the extraction result of the method with the traditional classification method, in
which show ANFIS's better performance.
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This paper makes a study of maximum a posteriori (MAP) estimation method for enhancing the spatial resolution of a
hyperspectral image using a higher resolution coincident panchromatic image. Here, the mathematical formulation of the
proposed MAP method is described and the detail process step is introduced. Then, enhancement results using PHI
hyperspectral image datasets are provided. In general, it is found that the MAP method is able to obtain high-resolution
hyperspectral data. Experiment shows that the method is effective while the enhancement for conventional methods, like
average estimation, is limited primarily to fuse spectral information.
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This paper studies the practical generation of Voronoi diagrams of multiply-connected planar areas bounded by straight
line segments. The key idea of the algorithm consists in calculating Voronoi polygon of every Voronoi object in planar
areas independently. The main approach is divided into two steps. The first step is to calculate all relevant bisectors of
the all Voronoi objects, and the second is to combine obtained bisectors into completed Voronoi polygons individually.
The contents of steps are both very important and all codes are implemented in Visual C++ platform. The resulting codes
are tested extensively on real-world data, and its practical running time seems to grow only linearly. Three statistical
CPU-consumption charts have been drawn with the Voronoi diagrams computation data. The CPU-time consumptions
records also gain the advantages over other published codes for computing Voronoi diagrams. The development of the
algorithm is achieved by treating equidistant generation as a locus-tracing problem.
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With the rapid growth of image archives, many content-based image retrieval and annotation systems have been
developed for effectively indexing and searching these images. However, due to the semantic gap problem, these
systems are still far from satisfactory for practical use. Hence, bridging the semantic gap has been an area of intensive
research, in which several influential approaches that based upon an intermediate representation such as bag-of-words
(BOW) have demonstrated major successes. In most previous work,, the semantic context between visual words in BOW
is usually ignored or not exploited for the retrieval and annotation. To resolve this problem, we have developed a series
of approaches to semantic context extraction and representation that is based on the Markov models and kernel methods.
To our knowledge, this is the first application of kernel methods and 2D Markov models simultaneously to image
categorization and annotation which have been shown through experiments on standard benchmark datasets that they are
able to outperform several state-of-the-art methods.
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Due to the inherent imperfections in the imaging process, fluorescence microscopy images often suffer from
spurious intensity variations, which is usually referred to as intensity inhomogeneity, intensity non uniformity,
shading or bias field. In this paper, a retrospective shading correction method for fluorescence microscopy
Escherichia coli (E. Coli) images is proposed based on segmentation result. Segmentation and shading correction
are coupled together, so we iteratively correct the shading effects based on segmentation result and refine the
segmentation by segmenting the image after shading correction. A fluorescence microscopy E. Coli image can
be segmented (based on its intensity value) into two classes: the background and the cells, where the intensity
variation within each class is close to zero if there is no shading. Therefore, we make use of this characteristics
to correct the shading in each iteration. Shading is mathematically modeled as a multiplicative component and
an additive noise component. The additive component is removed by a denoising process, and the multiplicative
component is estimated using a fast algorithm to minimize the intra-class intensity variation. We tested our
method on synthetic images and real fluorescence E.coli images. It works well not only for visual inspection, but
also for numerical evaluation. Our proposed method should be useful for further quantitative analysis especially
for protein expression value comparison.
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Nature reserves are facing a very challenging conflict between conservation and development today. The protection
effect of Jiuzhaigou Nature Reserve has received considerable attention, especially in view of its stimulating tourism
after the 1990s. Remote sensing data from 1974, 1994 and 2002 were chosen for the analysis of this reserve, since they
closely represented the vegetation situation before and after felling, as well as the disturbance from the flush of tourism.
We find that the quality and quantity of the forest in Jiuzhaigou Nature Reserve continues to decline, owing to the
conifer area and whole forest area constantly shrinking, as well as the landscape fragmentation increasing. The rate of
loss of forest in the second period (1994-2002) had showed down much than that in the first period (1974-1994), due to
nature protection. Shrubland area continued to increase throughout the two periods, with an increased speed in the
second period which was about 3.5 times that in the first period. The treeline was consistently retreating, contributing a
total of 467.96 ha of conifer forest lost. However, the causes involved in tree mortality and the resulting regression of the
treeline are not clear. In any case, under the general background of global warming, human impact undoubtedly should
have direct or indirect cause dramatic consequences for the forest in this very sensitive zone, while there are many
uncertainties in the behaviour of high mountain ecosystems.
Keywords: Jiuzhaigou Nature Reserve, Vegetation, Habitats fragment,
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Global motion estimation (GME) has attracted great attentions because of its broad applications in video coding, image
stabilization, object segmentation and detection. In this paper, Fourier transform formula of the image after global
motion with a 6-parameter affine model is deduced, and its special cases for the 4-parameter and 5-parameter affine
model are discussed. A method for the global motion estimation using the 5-parameter affine model is proposed based on
the Fourier transform properties of the tow images before and after global motion. Simulation results show that the 5
affine parameters can be satisfactorily estimated.
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Thin-plate spline (TPS) model has been utilized in fingerprint match to deal with nonlinear deformation by Bazen and
Gerez in 2002. The matching algorithm is composed of two parts, the local match and the global match. In local match,
candidate corresponding points from two minutia sets are obtained by local triangle match which is used for generating
TPS model in global match. However, not all candidate pairs are true corresponding ones in prints, and the spurious pairs
influence the final results. Here we present a novel matching scheme that inserts the graphical model-based confirming
process between the local match and the global match. This middle process not only minimizes the effects of spurious
matched pairs, but also provides the reliable degree of candidate pairs used for similarity. Experiments on databases of
FVC2004 achieve the good performance.
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With the development of spatial, temporal and spectral resolution of remote satellite imagery, the data acquired in the
orbit must be compressed to meet the requirement of the real-time data downlink transmission. When the satellite data
are transmitted in the downlink space channel, error code may be produced as a result of external interference. The error
code will cause serious diffusion problem for the transmission of compressed data. According to the principle of the
error control encoding and decoding, as well as the corresponding recommends of consultative committee for space data
systems (CCSDS), a set of error control algorithm and scheme is proposed to satisfy the requirement of remote sensing
satellite data transmission, combining the data compression practice. The emulation experiments show that the method is
effective for preventing and reducing the error diffusion, so as to provide reliable data for the technique processing in the
fields of remote sensing.
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The traditional error resilience technique has been widely used in video coding. Many literatures have shown that with
the technique's help, the video coding bitstream can been protected and the reconstructed image will get high
improvement. In traditional techniques, the bitstream is segmented to packets and the encoder is reset at the beginning of
each packet. The initialization will significantly reduce the coding efficiency. In this paper, we propose a new technique
to improve the error resilience using concept of disharmony degree in both spatial and temporal domain. This new
concept compares the pixels' difference in the spatial filed and temporal field, which helps retain the correctly decoder
within the bitstream improving the quality of the reconstructed image. Experimental results show that with the new
resilience technique help, the efficiency of error resilience improves the quality of reconstructed image and the detection
ratio of error blocks.
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The traditional error resilience technique has been widely used in video coding. Many literatures have shown that with
the technique's help, the video coding bit stream can been protected and the reconstructed image will get high
improvement. In this paper, we review the error resilience for video coding and give the experiment of this new
technology. These techniques are based on coding simultaneously for synchronization and error protection or detection.
We apply the techniques to improve the performance of the multiplexing protocol and also to improve the robustness of
the coded video. The techniques proposed for the video also have the advantage of simple trans-coding with bit streams
complying in H.263.
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Cognitive radio is a kind of intelligent and spectrum sharing technology for improving the utilization of spectrum. It can
detect primary user by sensing empty spectrum bands. Due to shadowing and multi-path fading, the reliability of single
terminal detection is low. Information fusion algorithm based on collaborative spectrum sensing can improve the sensing
performance significantly. In this paper, a high performance information fusion algorithm has been studied on the basis
of analyzing several classic fusion algorithms. We drive the expression for the probability of the detection and the falsealarm
for this fusion algorithm. Simulating results indicate that the fusion algorithm presented in this paper achieves
better detection performance than traditional fusion algorithms.
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This paper describes 360 degree viewing display system that can be viewed from any direction. A conventional
monitor display is viewed from one direction, i.e., the display has narrow viewing angle and observers cannot view
the screen from the opposite side. To solve this problem, we developed the 360 degree viewing display for
collaborative tasks on the round table. This developed 360 degree viewing system has a liquid crystal display
screen and a 360 degree rotating table by motor. The principle is very simple. The screen of a monitor only
rotates at a uniform speed, but the optical techniques are also utilized. Moreover, we have developed a floating
360 degree viewing display that can be viewed from any direction. This new viewing system has a display
screen, a rotating table and dual parabolic mirrors. In order to float the only image screen above the table, the
rotating mechanism works in the parabolic mirrors. Because the dual parabolic mirrors generate a "mirage"
image over the upper mirror, observers can view a floating 2D image on the virtual screen in front of them. Then
the observer can view a monitor screen at any position surrounding the round table.
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In fingerprint verification or identification systems, most minutiae-based matching algorithms suffered from the
problems of non-linear distortion and missing or faking minutiae. Local structures such as triangle or k-nearest structure
are widely used to reduce the impact of non-linear distortion, but are suffered from missing and faking minutiae. In our
proposed method, star structure is used to present local structure. A star structure contains various number of minutiae,
thus, it is more robust with missing and faking minutiae.
Our method consists of four steps: 1) Constructing star structures at minutia level; 2) Computing similarity score for each
structure pair, and eliminating impostor matched pairs which have the low scores. As it is generally assumed that there is
only linear distortion in local area, the similarity is defined by rotation and shifting. 3) Voting for remained matched
pairs according to the compatibility between them, and eliminating impostor matched pairs which gain few votes. The
concept of compatibility is first introduced by Yansong Feng [4], the original definition is only based on triangles. We
define the compatibility for star structures to adjust to our proposed algorithm. 4) Computing the matching score, based
on the number of matched structures and their voting scores. The score also reflects the fact that, it should get higher
score if minutiae match in more intensive areas. Experiments evaluated on FVC 2004 show both effectiveness and
efficiency of our methods.
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Geomagnetic field is the basic physics field of the Earth, which can't be destroyed or changed in the foreseeable
future. Geomagnetic field don't require special service, therefore, it can be considered as a solid source of navigation
information. The key technologies of geomagnetic navigation are still looking for high accuracy mapping and high
accuracy geomagnetic field measurement on board aircraft, The article analyses some kinds of geomagnetic models.
according to the character of the geomagnetic models, The NGDC-720 model is used as reference map preparation. The
model with Kriging method give birth to the reference maps which include geomagnetic seven vectors' map (X, Y, Z, F, D, I, H). Using the reference maps, The geomagnetic vectors'statistical characters have been analyzed. According to the
statistical characters, some changeable obviously statistical characters can be used as matching characteristic values.
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In this paper mid-term infrared (IR) emission anomalies related to medium or large earthquake using wavelet
time-frequency analysis method have been detected using OLR(Outgoing Longwave Radiation) daily grid data (2.5°)
for Sichuan-Yunnan area. Our analysis of OLR mean value(25 points totally) about Sichuan-Yunnan study area from
2000 to 2008 using wavelet time-frequency analysis shows obvious peaks in the scale of 0-0.2 years. The peaks appeared
in the latter half of 2002 and 2007. It can be found that nine earthquakes (Ms>6.0)had happened in Sichuan-Yunnan
region during this period, and these earthquakes mainly concentrated in 2003 and 2008. The OLR anomalies in 2002 and
2007 can be thought as precursors for earthquakes in 2003 and 2008, respectively. The anomalies are mainly occurred on
half a year to one year before earthquakes. And the anomalous points in twenty-five studied points are near the
epicenters. It indicates that there are relationship between earthquakes and OLR anomalies which can be detected by this
method. It is possible to identify some mid-scale anomalies before occurrences of medium to large earthquakes by using
this method. The result of this study will provide reference to mid-term earthquake prediction.
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The paper reviews the complexity of the natural geological conditions, the ecological environmental frail and the poor
conditions of wired or wireless communications coverage in the Three Gorges reservoir area, as well as the emergent
geological disasters commanding platform. As an important part of emergency geological disasters rescue system, the
long-distance video conferencing system can meet the demands, upon which the system architecture design and network
analysis it can be achieved based on H.323, and also gives the data flow analysis. The spot test shows that the design of
this system is reliable, security and strong, of which the voice is clear, the images are smooth and the data transmission is
stable.
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A mask-based image blending approach is presented and implemented on mobile devices for producing mobile
panoramic images. In this approach, a single channel mask is created and initialized with distributed values for
each source image. It is warped and interpolated together with its source image during panorama stitching to keep
related transformation information. The values of the mask provide weighting coefficients for blending images
together to produce a panoramic image. Compared to other complicated approaches such as gradient domain
image blending, its computational and memory cost is low. Compared to other simple approaches such as alpha
blending, it does not need to locate boundaries of overlapping areas for determining weighting coefficient values.
It can also be applied to 2D panorama stitching and its blending quality is better. The approach is implemented
in a mobile panorama system to produce panoramic images for preview. It shows good performance in processing
image sequences captured in both indoor and outdoor scenes. The property in low computational and memory
costs as well as fast blending speed of the approach really benefits the mobile panorama system.
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This paper presents an algorithm for lossless information hiding based on linear prediction template, devotes every effort
to reduce the prediction error of linear prediction template, since reducing the prediction error in deeper degree results in
better effects of improving embedding capacity and image quality. Here we also study how much does certain threshold
value of linear prediction template affect embedding capacity and image quality. Since there should be many threshold
values specification, here we take the destined threshold values for comparison, and presents simulation experiment
results. Using linear prediction template and extended embedding/extraction algorithms, the algorithm utilizes the
relativity among the adjacent pixels sufficiently to implement information hiding and blind extraction with satisfaction.
The experiment results indicate that large quantity information can be embedded while keeping less impact on image
quality of information hided ones. Application fields of this algorithm should include circumstances when large hiding
data quantity, high precision is required, like image storing and illustration, copy protection, remote sensing, military,
medicine, law, etc.
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In this paper, we present a new copyright information hide method for digital images in Moiré fringe formats. The
copyright information is embedded into the protected image and the detecting image based on Fresnel phase matrix.
Firstly, using Fresnel diffraction transform, the random phase matrix of copyright information is generated. Then,
according to Moiré fringe principle, the protected image and the detecting image are modulated respectively based on the
random phase matrix, and the copyright information is embedded into them. When the protected image and the detecting
image are overlapped, the copyright information can reappear. Experiment results show that our method has good
concealment performance, and is a new way for copyright protection.
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The forest ecosystem in Northeastern China (NEC) is approximately 25% proportion of total forested area of China,
which has been undergoing dramatic changes due to massive loggings and forest fires in the last several decades and
successively intensive manual afforestation and closing protective recovery since 1990s. It is a hot region for scientific
research in carbon balance. In this paper, national land cover GIS data, moderate resolution imaging spectroradiometer
(MODIS) imagery, and vertical waveform of Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and
Land Elevation Satellite (ICESAT) were combined together to map forest aboveground biomass (AGB) in the NEC.
Firstly, GLAS waveform has the advantage of three dimensional observations and can play the role as sampling
footprints for forest biomes. The estimation algorithm was developed between field survey samples and height profile
indices of GLAS waveform to predict forest AGB by neural net regression model. The correlation coefficient R2 between
GLAS forest AGB and field-investigated ones was 0.73. Secondly, MODIS data affords spatially continuous images and
can be used to stratify forested regions as statistical districts. one hundred of spectral clusters were derived from MODIS
phenological curve of enhanced vegetation index (EVI) and near infrared (NIR) channel by K-Means method and
stratified for the statistics of GLAS forest AGB samples. The result illustrates spatial pattern forest AGB and explores its
total amount in the NEC.
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In this paper, with the auxiliary of old GIS vector data, a routine for roads changing detection is proposed: find
enough road center points firstly using the dynamic binary templates matching, then remove the noise points
With the Hough transformation, Artificial Neural Network or even the Active Contour Model (Snakes), based
on the extracted points, try to searching new road points as many as possible with the the templates matching,
and last get the changes information along each road by judging the distance between the old road polylines and
the newly extracted points. Experiments prove that this routine is effective to detect the change of roads in the
image.
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The goal of image inpainting is to restore the damaged or missing pixels on images and it is an active research topic in
image engineering. In order to restore narrow gaps on damaged images, we propose a type of anisotropic inpainting
model based on Markov Random Fields. The inpainting model can preserve the edges and orientational texture. We
implement our method using Simulated Annealing algorithm. Experiments show that the proposed method can obtain
satisfying results and is practical in applications.
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It is difficult to meet both direction and curvature constraints for traditional Fast Marching (FM) method in path
planning. Based on adjusting the cost function in Eiknoal equation-the control equation for FM, a new model for
computing the integrated cost function was presented in this paper. A relationship formula about curvature radius was
obtained and three kinds of adjusting strategies were given; two of them were used to modify the route to meet with the
requires of turning constraint in this paper. Experiments showed that the improved model can be used to plan the path
with FMM for agent such as unmanned aerial vehicle (UAV) or robot, which is limited to pass through the scene
matching areas. And our preliminary experiments demonstrated that the strategies are feasible and efficient to obtain
path with certain curvature radius. The model can also be used to represent the problem such as an aircraft flying in a
flow field.
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Compressive sensing (CS) is a theory about that one may achieve a nearly exact signal reconstruction from the fewer
samples, if the signal is sparse or compressible under some basis. The reconstruction of signal can be obtained by solving
a convex program, which is equivalent to a LASSO problem with l1-formulation. In this paper, we propose a stage-wise
fast LASSO (StF-LASSO) algorithm for the image reconstruction from CS. It uses an insensitive Huber loss function to
the objective function of LASSO, and iteratively builds the decision function and updates the parameters by introducing
a stagewise fast learning strategy. Simulation studies in the CS reconstruction of the natural images and SAR images
widely applied in practice demonstrate that the good reconstruction performance both in evaluation indexes and visual
effect can be achieved by StF-LASSO with the fast recovered speed among the algorithms which have been
implemented in our simulations in most of the cases. Theoretical analysis and experiments show that StF-LASSO is a CS
reconstruction algorithm with the low complexity and stability.
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This paper presents a strong noise image enhancement method based on intrascale dependencies of the second
generation curvelet transform. Observing that the immediate four neighbor coefficients bear the most important
dependencies, we use spatial clustering property of the intrascale neighbor coefficients to separate noise and signal of
interest, and to deal with them differently, i.e. to suppress noise and strengthen edges. Comparing our approach with
Starck's enhancement model (Starck et al., 2003), we experimentally find that for high noise level images, our method
outperforms the starck's system in noise suppression and signal strengthening and produces better enhancement results.
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Based on Particle Filter, Gravity Gradient-Terrain aided position technology is proposed in this paper. With the
sensitivity of gravity gradient to terrain, the gravity gradient reference map can be computed from the local terrain
elevation data. The position can be actualized through matching the real-time measured gravity gradient data to the
prepared gravity gradient reference map. The most widely used approximate filtering method is the extended Kaman
filter (EKF). EKF is computationally simple but, the convergence of the state estimation for the position is not
guaranteed. Particle filter (PF) makes use of the non-linear state and measurement functions, no linearization technology
is needed. PF can assure the convergence of the state estimation which follows from the classical results on convergence
of Bayesian estimators. Simulations have been done and Particle filter has been shown to be a superior alternative to the
EKF in the gravity gradient-terrain matching navigation systems.
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Instrument display panel is one of the most important parts of automobiles. Automatic detection of LED
signal lamps is critical to ensure the reliability of automobile systems. In this paper, an automatic detection
method was developed which is composed of three parts in the automatic detection: the shape of LED lamps,
the color of LED lamps, and defect spots inside the lamps. More than hundreds of fascias were detected with
the automatic detection algorithm. The speed of the algorithm is quite fast and satisfied with the real-time
request of the system. Further, the detection result was demonstrated to be stable and accurate.
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A new path planning method for UAV in static workspace is presented. The method can find a nearly optimal path in
short time which satisfies the UAV kinematic constraints. The method makes use of the skeletons to construct the graph
of the planning space considering the configuration of the obstacles and utilizes the graph to find a shortest collision-free
path, and a novel technique is utilized to convert the free path into a feasible path. The method can be applied to different
applications and easy to be implemented. Experimental results showed that the path planning can be done in a fraction of
second on a contemporary workstation (2-3 seconds) under the condition of satisfying the kinematic constraints.
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Agricultural pollution, which has a direct impact on the water, soil and air quality, is a common but increasingly
serious environmental problem nowadays. The misusage of fertilizer, high application fertilizer and low utilization rate,
are the major factors of the pollution. Therefore, the pollution caused by nitrate nitrogen has posed a very serious
problem to the ecological environment. Combined with the GIS technology, this paper takes Majiang County in Guizhou
province that is at southwest of China as a case, to carry out the research on the calculation of the nitrogen surplus in
paddy field and the dry land based on the farmland nutrient balance model using the fertilizer amount. This paper reveals
the spatial distribution characteristic of the nitrogen pollution, which can help to find a reasonable crop cultivation and
fertilization methods to increase the effective utilization fertilization and therefore reduce the pollution.
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The satellite imaging system is affected by optical diffraction limitation, atmosphere disturbance, CCD under-sampling
noise and etc. Then the information beyond image system cut-off frequency is lost, images degrade and spatial resolution
decrease. Structure information becomes undistinguishable, which is fatal to manual interpretation and adaptive target
recognition. In this paper, one structure information preserved scheme is proposed. Taking into account the anisotropic
diffuse property of PSF (point spread function) of in-track and cross-track direction, the sparse property of nature image
and noise level, with data-driven kernel function sub-pixel estimation, the method restore high spatial resolution image
from low one. Joint frequency domain and wavelet domain L1 normal regularization suppress wrinkle and noise
amplified for this ill-posed inverse problem. With CBERS-2 images, this method is proved to improve spatial resolution
and preserve edge and structure effectively without obverse wrinkle. With MTF curve, the spatial resolution is improved
obviously with high PSNR, and the edge is preserved perfectly.
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This work is the case study based on the remote sensing data about squall line in Shanghai at July 12 2004, focus on the
analysis on Doppler radar echo products, satellite image, surface and sounding data, automatic weather station data. The
purpose is to reveal the special structure of the squall line, recognize the evolution of strong convection with multi-scale
information, and find the prediction mechanism for reducing disaster on mankind.
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A digital holographic reconstruction in the frequency and spatial domain is presented in this paper. This
technique applies Fourier transform on heterodyne hologram with interference fringes then the complex amplitude
and phase information are extracted from its sidebands. Reconstruction of the phase and amplitude image is
completed through inverse Fourier transform back to spatial domain. For best holographic reconstruction qualities,
a blind deconvolution filtering and an image based autofocus spatial processing are also adopted and discussed.
Experiments show satisfying reconstruction results.
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The traditional image quality assessment methods based on pixels have many limitations. Such as the lack of
consideration of the image structure, or the need of a complete reference image. To avoid these problems, this paper
presented a new image quality assessment method based on weighted singular value decomposition in wavelet domain
(WWSVD). In this algorithm, the singular value vector difference and the mean bias between the original image and the
distorted image are considered to evaluate the distortion degree. Many tests were conducted to evaluate the performance,
the 227 testing images of JPEG2000 compression were come from the Live Image Quality Assessment Database,
Release 2005. The results showed a great improvement in both the consistency with the DMOS (Differential Mean
Opinion Score, DMOS) and the stability when applied to a large range of compression rates.
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Technology of interference becomes more advancing. Adopting fog and aerosols is the best way to interfere optical
detection. Due to the fog and aerosols, target recognition becomes difficult under this environment. In the present paper a
method is given to solve this problem in a simple way.
A dual-wavelength technology used in anti-interfere for long range and short distance detection is introduced in this
paper, which can discriminate the backscattering reflection of fog and aerosols. In the present work the scattering
character of the special fog and aerosols environment is calculated using the Rayleigh scattering method and Mie
scattering method. The scattering characters in different environment are analyses using two wavelengths, i.e. one
wavelength lies in ultraviolet wave band, the other in near infrared wave band. The results indicated that the ratio of
proportion-discrimination is usually greater than 2, and deeper the strength of the fog and aerosols, the greater the ratio.
This method also validated by experiment. In the present study, three kinds of wavelength such as 405nm, 670nm and
808nm are adopted. The intensity data collected shows that the ratio is greater than 3.
The performance and working principle of the system and its components are analyzed in details. Based on the full
system, the dual-wavelength technology can be well applied. The result of the experiments also proves that the
technology is efficient, especially in the heavy fog and aerosols environment.
The dual wavelength method can be used for long range and short distance detection.
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The aerosol optical depth was affected by the chemical composition, the particle size and the shape of aerosol as well as
the water vapor in the atmosphere; it is an important indicator for air pollution. The special and temporal characteristics
of aerosol optical depth (AOD) was measured by CE318 sun-photometer, Angstrom wavelength exponent (Alpha) and
the aerosol turbidity coefficient (β) were calculated in Ningbo, Lin'an and Qiandaohu of Zhejiang province from 2007 to
2008. We also analyzed the relationship between AOD and Angstrom wavelength exponent (Alpha) in these stations.
The results show that there are different pattern of AOD in this gradient of urban and suburban region. Lin'an station had
two peaks of AOD, but Ningbo and Qiandaohu stations had single peak of AOD in measurement year. The difference of
AOD seasonal pattern exists in three sites. The Angstrom wavelength exponent (Alpha) analysis suggests that the aerosol
sizes in three stations various from fine particle in autumn to coarse particle in spring. The seasonal patterns show that
spring air pollution is serious, summer is relatively clean, and autumn and winter are relative serious in three stations.
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This paper mainly discusses the urban design factors how to affect the urban heat environment in urban residential area
by remote sensing. The discussed urban design factors include floor area ratio, building height, green area ratio, and
population density. The results indicate that when the green area ratio in residential area becomes 40%, the effect of
weakening UHI is best. Higher than 40%, the effect of reducing the temperature begins to decline. The higher the
residence buildings are, the higher the mean surface temperature of residential districts is. When floor area ratio ranges
from 1.5 to 3, the change of mean surface temperature is abrupt. When floor area ratio is greater than 3, the growth of
mean surface temperature would be slower. Surface temperature and population density have logarithm relationship.
Overall, planners have the opportunity to gain significant insight into the physical manifestations of planning policies
within cities by integrating quantitative analysis of electromagnetic energy measurements collected by remote sensing
systems. Remote sensing would be a useful tool for planners to make scientific decisions.
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A novel approach is proposed to estimate the parameters of rotational motion blur. Firstly, the rotational blur was
changed into translational motion blur by geometric transformation from Cartesian coordinate system to polar coordinate
system. The characteristic of the translational motion blurred image in frequency domain was concluded. Then, the
characteristic was further analyzed by a new definition of point spread function (PSF). Based on this, an object function
was derived to describe the relationship between the parameter and the characteristic. At last, the statistical optimal
parameter of the blur motion was obtained by traversing through the resolution space of the object function. The
comparing experiment results demonstrate that the new method has better accuracy than traditional ones.
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Unreasonable decision-making results and unavailable stability analysis are the main drawbacks of current connection
numbers ranking methods. The novel ranking methods based on the relative certain probability power, relative optimistic
probability power and relative pessimistic probability power were proposed in this paper to overcome these
disadvantages. The permissible range of uncertain evolution factor which maintains the stability of the sorting among
connection numbers was calculated as well. The numerical computation results indicated the effectiveness of the
proposed ranking methods.
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In this paper, a semi-fragile watermark solution based on quantization index modulation in the wavelet region was
proposed. The algorithm employs a compressed halftoned binary image as watermark and embeds it in the wavelet
domain through quantization index modulation, which can not only identify the authenticity of the content of digital
image, but also recover the tampered image approximately. Because the watermark is a low-resolution original image,
which carries the original image information, so the original image is not required when authenticating, and the tampered
region can be recovered according to the watermark. The method can tolerate a certain degree of compression distortion
or noise. Beside, a secret key is used to select the embedded watermark bits and their embedded positions to increase the
security of watermarking. Experimental results show this semi-fragile watermarking algorithm is effective and practical
for content authentication.
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After a deep analysis on how to use an image processing system to detect the missing holes on the motor carling, we
design the whole system combined with the actual production conditions of the motor carling. Afterwards we explain the
whole system's hardware and software in detail. We introduce the general functions for the system's hardware and
software. Analyzed these general functions, we discuss the modules of the system's hardware and software and the
theory to design these modules in detail. The measurement to confirm the area to image processing, edge detection,
randomized Hough transform to circle detecting was explained in detail. Finally, the system result tested in the laboratory
and in the factory is given out.
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As the scientific investigation on the Ms8.0 Wenchuan earthquake demonstrates, the landscapes of co-seismic surface
ruptures or structure destructions were rapidly destroyed by storms or secondary disasters. Traditional survey methods
often are limited by the environment and do not provide perfect information about the deformation value in a timely
manner. The 3D laser scanner, on the other hand, can work under varying light conditions and does not require contact
with the destroyed objects. Its prompt completion of a pan-shot makes it possible to efficiently record a wealth of
information about the earthquake deformations, ensuring the quantitative analysis of related data. Its disadvantages
include costliness, unwieldiness and high-temperature-environmental inadequacy, etc.
In this paper, focusing on some examples, we explore the characteristics of 3D laser scanning technology used in the
micro-geomorphology survey and discuss its advantages and limitations. We also describe the data processing methods
and results. This includes the deformation values of the co-seismic surface ruptures or the merged impressions by 3D
scanning data and full view photo. In conclusion, 3D laser scanning has a wide range of prospects in
micro-geomorphology surveying and earthquake investigation. We then make some proposals such as using wireless
transmission that can improve its environmental adaptability.
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An efficient algorithm for computing 24-point DFT, which can contribute fast algorithms to more N-point DFTs, is
developed. The computation of one 24-point DFT requires only 24 real multiplications and 252 real additions. According
to the principles of decimation-in-time (DIT) or decimation-in-frequency (DIF) algorithm and the efficient algorithm of
24-point DFT, 2M×24, 4M×24, 576=24×24 and 24×M-point DFT have their own efficient algorithms, respectively. The
computational requirements of computing N=2M×24-point and N=4M×24-point DFT in their own efficient algorithms
based on 24-point DFT block are (2M+1/6)N+20 real multiplications and (3M+31/3)N+4 real additions, (3M+1/3)N+16
real multiplications and (10.5-1/6+5.5M)N+4 real additions, respectively, while the computational requirements of
576=24×24-point DFT is 3184 real multiplications and 13140 real additions. In this paper, all of algorithms based 24-
point DFT block are derived and analysed, but their practical applications need to be further explored.
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For automatic service composition, a planning based framework MOCIS is proposed. Planning is based on two major
techniques, service reasoning and constraint satisfaction. Constraint satisfaction can be divided into quality constraint
satisfaction and quantity constraint satisfaction. Contrary to traditional methods realizing upon techniques by interleaving
activity, message and provider, the novelty of the framework is dividing these concerns into three layers, with activity
layer majoring service reasoning, message layer for quality constraint and provider layer for quantity constraint. The
layered architecture makes automatic web service composition possible for activity tree that abstract BPEL list and
concrete BPEL list are achieved automatically with each layer, and users can selection proper abstract BPEL or BPEL to
satisfy their request. And E-traveling composition cases have been tested, demonstrating that complex service can be
achieved through three layers compositing automatically.
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Radio Frequency Identification (RFID) technology has been widely used in the image recognition system. However, the
feature of the RFID system may bring out security threatens. In this paper, we analyze the existing RFID authentication
protocols and state an infinite dimension pseudo random number generator to strengthen the protocol security. Then an
authentication protocol based on infinite dimension pseudo random number generator is proposed. Compared to the
traditional protocols, our method could resist various attack approaches, and protect the tag information and the location
privacy of the tag holder efficiently.
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SAR simulation imaging may be useful for several purposes, and this paper focuses on the use of SAR image simulation
for accuracy analysis of image aid navigation in natural scene. However, natural scenes are more complicated including
randomly and anisotropic distributed. So the anisotropic fBm interpolation mold was proposed via improving fBm
method for obtaining a more accurate matrix of the DEM data. On the basis of high-resolution DEM data, an approach
was presented to SAR imaging simulation for comprehensive scenarios, which takes account scattering, shadowing and
the layover. In the simulation experiment, this algorithm was successfully implemented on producing SAR simulation
imaging, and can satisfy the requirements of accuracy analysis in SAR aid navigation system.
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The authors have researched support system of the reminiscence and life review activity. This support system
consists of an interactive tabletop display and interface system. On the reminiscence and life review activity, a
therapist puts pictures on the table so as to trigger a talk. However some observers may perceive upside down
images if they sit down opposite the therapist. To overcome this problem, we have developed the display system
which can be viewed from any direction. In this paper, we propose a 4-views display system and a 360 degree
viewing display for cooperative activity on a round table.
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In this paper, the joint distribution of the Nonsubsampled Contourlet Transform coefficients is studied. It is found that
the estimation of the joint distribution is implement impossible due to the complex of joint empirical distribution
function and dependence of NSCT coefficient vector components. To distinguish different joint distributions of different
images, the sample covariance matrix feature is proposed. The texture retrieval experiment is conducted in order to
evaluate the performance of the sample covariance matrix feature. The result shows that the proposed feature is efficient
in representing the texture and the difference of the joint distribution of the Nonsubsampled Contourlet Transform
coefficients.
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The ROI based video coding is widely applied in video communication. In this paper, we propose a multilevel ROI
model, which includes the eye-mouth core region (CR), the face profile region (PR), the edge region (ER) and the
background region (BR), to classify the subjective importance level of regions for the scene. Taking account of the
proposed model, we first segment the current frame into four regions through skin color detection and feature location.
Then, we improve the rate control algorithm in JVT-G012 proposal. We consider two factors, including subjective factor
by our multi-level ROI model and objective factor by direct difference from reference frame, to model the complexity
weight of each macroblock (MB).We allocate resources both at the frame layer and the basic unit layer, and adjust QP at
MB layer. Finally, we restrict the QP of MB with three strategies to maintain the spatial and temporal smoothness. The
experimental results illustrate that PSNR of ROI (CR plus PR) area using proposed method is in average over 0.5dB
higher than JM8.6, while there are only slight changes in the PSNR of whole frame between two methods. Subjective
quality based on our method also achieves much better performance.
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In this paper, we develop an auto-focus algorithm using a new sharpness function. Different from other sharpness
functions used for auto-focusing in the past, the new defined sharpness function is more robust to noise, jitter of the
camera. In order to test the algorithm, a modified hill climbing algorithm is used in the experiments to find the focused
lens position and the experimental results show that the new auto-focus algorithm based on the new sharpness function
has better performance.
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In this paper, a hyperspectral image lossy coder using three-dimensional Embedded ZeroBlock Coding (3D EZBC)
algorithm based on Karhunen-Loève transform (KLT) and wavelet transform (WT) is proposed. This coding scheme
adopts 1D KLT as spectral decorrelator and 2D WT as spatial decorrelator. Furthermore, the computational complexity
and the coding performance of the low-complexity KLT are compared and evaluated. In comparison with several stateof-
the-art coding algorithms, experimental results indicate that our coder can achieve better lossy compression
performance.
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The authors have researched a support system of the reminiscence and life review activity. This support system
consists of an interactive tabletop display and interface system. Many interaction systems are proposed until
now. An invisible code is one of the useful technologies for a computer interaction. The invisible codes provide
us with an operating environment using a pen-like device. However, this technology is applied to the only paper
media. The authors think we want to realize an interaction using the invisible code on an electrical media. In
this paper, we propose a method to display invisible codes using LCD panels and to detect a polarized symbol
image with a conventional CCD camera.
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H.264 is the newest video coding standard and is currently one of the hot subjects of video processing technologies.
Coding quality and compression ratio have been greatly improved in the new standard compared with the previous
standards. The context-based adaptive technology is introduced into the new standard, which can be said to be a
technology renovation of the video coding. The main entropy coding technologies of H.264 include VLC (Variable-
Length Coding) and CABAC (Context-based Adaptive Binary Arithmetic Coding). CAVLC is VLC and adopts the
context-based adaptive technology, therefore the coding efficiency is greatly improved. Currently, the design of the
CAVLC encoder is mainly in software method, but with the development of real-time video processing technology, it is
difficult for software to meet the demands. As a result, the hardware method in designing of CAVLC coder becomes a
good choice. In the paper a CAVLC entropy encoder architecture based VLSI is proposed and implemented on an Altera
FPGA device. As the results of simulation and synthesis, it can process 4×4 or 2×2 blocks per 16 clock periods with
pipelined architecture and can achieve the real-time processing requirement of 30 frames per second for a 720×480 video
at 100 MHz operation frequency.
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We proposed a novel framework on how to improve the compression performance through the idea related to the
decreased spatial resolution down-sampled by the LP (Laplacian Pyramid) transform, and only code the low-pass band.
Before being compressed, our method intentionally down-sampled the image as part of the pre-processing step, and then
applies the directionlet interpolation as post-processing step of the compressed image. At low bit-rates an appropriately
down-sampled image compressed using multi-codec and later interpolated via directionlet, can be visually and
objectively better than the image compressed directly with the codec scheme at the same number of bits. Down-sampling
and up-sampling play a key role in our proposed novel code means which support spatial scalability. This scheme can be
utilized to efficiently optimize the overall quality of the reconstructed image, especially the rich textures or edges
preservation. We compared with the conventional JPEG2000 coding method and showed our framework can get
comparable good results at low bit rate and is independent with the coding method.
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In this paper, we consider lossy image compression, which is based on wavelet theory. We introduce image restoration
technology into the wavelet compression. By applying image restoration to the low-frequency component obtained by
entropy decoding in decompression process, we retrieve a gained high-frequency component, which is the expression of
reconstructed image texture in frequency domain. As a benchmark, the algorithm we present is compared to the
traditional wavelet compression. The results of comparative experiments show that our method performs better than
traditional algorithms. The PSNR in our method is elevated generally, and the reconstructed image is more texture-richer
than the traditional approach without restoration.
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Content-Based Image Retrieval (CBIR) is an important research topic of information retrieval,
involved in computer graphics, image processing, data mining and pattern recognizing. To make
content-based image retrieval suitable large-scale image database, we develop an effective dynamic
hierarchical clustering index scheme. Although this system uses a hierarchical clustering technology, with
the increasing in the number of cluster centers, it is slow to find the centers, and it becomes a system
performance bottleneck. In this paper, content features of image memory indexing is built. This method
effectively improves the retrieval speed without loss of the precision. Moreover, the clustering model was
improved, integrating the content features and textual features of image, which greatly improve the
accuracy of the clustering, thus significantly improves the system precision.
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By researching the Brushlet domain coefficients of texture images, we found that the distribution of the magnitudes of
Brushlet domain coefficients roughly meet rayleigh distribution. And there are correlations between Brushlet coefficients
in adjacent scales. Therefore, Rayleigh Mixture Model (RMM) is used to characterize the statistics of the magnitudes of
Brushlet coefficients. To capture the inter-scale persistence of Brushlet coefficients, a "four to four" models with markov
property is adopted in this paper. On the basis, by combining with the multi-scale Bayesian segmentation method, we
propose a multiscale Bayesian texture segmentation algorithm that is based on a Brushlet domain hidden Markov tree
(BruHMT) model. The experiment results indicate that our method is feasible and effective. Especially for coarse texture,
our method is superior than texture segmentation method using Wavelet domain hidden Markov tree (WHMT) model.
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A digital watermarking technique is a specific branch of steganography, which can be used in various applications,
provides a novel way to solve security problems for multimedia information. In this paper, we proposed a kind of
wavelet domain adaptive image digital watermarking method using chaotic stream encrypt and human eye visual
property. The secret information that can be seen as a watermarking is hidden into a host image, which can be publicly
accessed, so the transportation of the secret information will not attract the attention of illegal receiver. The experimental
results show that the method is invisible and robust against some image processing.
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In the application of machine learning, there is data imbalance problem generally. In view of multi-class imbalance
particularities, in this paper a new method named Multi-SVDD is proposed. And it is presented aimed to solving the
problem of multi-class imbalance based on the existing Support Vector Data Description (SVDD), which is used to solve
multi-class learning questions and the solution method for two-class imbalance problem. It was verified on the UCI data
set, and compared with multi-class classification method proposed. The experiment has indicated that the Multi-SVDD
algorithm is efficient when it is used to solve the multi-class imbalanced classification problems.
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RADARSAT 2 is used to estimate forest parameter. The study site is in Zhazuo forestry centre, Guizhou province,
China, where are mainly conifer species. Semi-empirical Water Cloud Model was used to estimate Leaf Area Index
(LAI). The result proved that using Water Cloud Model to estimate LAI is feasible. We use classical scatter model to
analyze the relationship between Tree Height and backscattering coefficients of different polarization mode or different
combinations of polarizations. And found that HH polarization is relatively sensitive to Tree Height, however, their
correlation is less than 0.6. It is shown that directly establish relations of backscattering coefficient or different
polarization combination and tree height to inverse LAI is not a desirable method.
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This paper presents the possibilities of extracting total potassium concentration in topsoil from Visible-near-infrared
(VNIR) spectra and reflectance of image data. Stepwise multiple linear regression (SMLR) and partial least-square
regression (PLSR) were used to select wavelengths which were highly correlated with the concentration of potassium.
For spectral measurements (from 400nm to 2480nm, at 2 nm increments) and chemical analyses, 70 topsoil (0~20 cm)
samples were collected in Tianjin City, North of China. Three methodologies of the reflectance spectra of topsoil
samples were employed: derivative reflectance spectra (FDR), inverse-log spectra (log (1/R)) and band depth (Depth).
According to the root mean square error of prediction (RMSEP), the best model was picked up. The optimal experiential
model (R=0.73, RMSEP=1.33) was achieved by PLSR method with parameter- log (1/R). Based on these credible
results, space distribution map of soil potassium concentration of Tianjin was drawn by ETM+ image. The coefficient
showed that the first and second bands of ETM were important for soil potassium concentration prediction. The
potassium concentration of seaboard is higher than that of inland area. Good prediction performance indicates that VNIR
spectra are potentially useful for rapid estimation of potassium concentration in topsoil, and inverse-log spectra (log
(1/R)) are the best parameter for prediction. Even the image data can be used for soil potassium concentration extraction
and the influences of the atmosphere and proper pre-processing are very important to prediction precision.
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According to the characteristic of noise in the laser exploration system, threshold circuit is often utilized in traditional
method, but the thresholds which are adopted in this kind of algorithm are not adaptive. When the circuit is confirmed,
the threshold is also confirmed, so the algorithm can not adapt the requirement of detecting weak signal in high noise.
This paper analyses how to choose the threshold of denoising based on noise features in laser exploration system, and
also analyses alterable MRA threshold method in details. The algorithm which is adopted in this paper solve the problem
of how to filter the noise whilst to keep the details of the signal. The result shows that the new algorithm has better
effect.
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Video shot boundary detection is a fundamental step for the organization of large video data. The classical VSB
detection is basically a sequential frame to compute frame-by-frame, however this approach is computationally very
expensive for large databases .In this work we propose a dichotomy approach for video shot boundary detection. The
proposed technique can improve the performance of the algorithm and reduce the calculation. Our experimental results
show that the proposed algorithm produces faster detection rapid.
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