In this paper a new deconvolution algorithm is presented concerning images contaminated by periodic stripes. Inspired
by the 2-D power spectrum distribution property of periodic stripes in the frequency domain, we construct a novel
regularized inverse filter which allows the algorithm to suppress the amplification of striping noise in the Fourier inverse
step and further get rid of most of them, and mirror-wavelet denoising is followed to remove the left colored noise. In
simulations with striped images, this algorithm outperforms the traditional mirror-wavelet based deconvolution in terms
of both visual effect and SNR comparison, only at the expense of slightly heavier computation load. The same idea about
regularized inverse filter can also be used to improve other deconvolution algorithms, such as wavelet packets and
wiener filters, when they are employed to images stained by periodic stripes.
Multi-channel scanning radiometer, on boarding FY-2 geostationary meteorological satellite, plays a key role in remote sensing because of its wide field of view and continuous multi-spectral images acquirements. It is significant to evaluate image quality after performance parameters of the imaging system are validated. Several methods of evaluating imaging quality are discussed. Of these methods, the most fundamental is the MTF. The MTF of photoelectric scanning remote instrument, in the scanning direction, is the multiplication of optics transfer function (OTF), detector transfer function (DTF) and electronics transfer function (ETF). For image motion compensation, moving speed of scanning mirror should be considered. The optical MTF measurement is performed in both the EAST/WEST and NORTH/SOUTH direction, whose values are used for alignment purposes and are used to determine the general health of the instrument during integration and testing. Imaging systems cannot perfectly reproduce what they see and end up "blurring" the image. Many parts of the imaging system can cause blurring. Among these are the optical elements, the sampling of the detector itself, post-processing, or the earth's atmosphere for systems that image through it. Through theory calculation and actual measurement, it is proved that DTF and ETF are the main factors of system MTF and the imaging quality can satisfy the requirement of instrument design.
Proc. SPIE. 6833, Electronic Imaging and Multimedia Technology V
KEYWORDS: Digital signal processing, Aerospace engineering, Imaging systems, Sensors, Imaging technologies, Signal processing, Charge-coupled devices, Analog electronics, Digital electronics, Prototyping
The novel visible nephogram imaging technology for polar orbit platform is demonstrated in the paper, and it could be
operated in from quarter moon to noon sunlight. The critical technologies and theirs solutions of the novel nephograph
are included: (i) the low light level imaging capability is achieved by the combination of time delay and integration
charge coupled device (TDI CCD) with push-broom imaging method; (ii) the large field of view capability is
implemented by the combination of 3 pieces of imaging module with smaller field of view; (iii) the wide dynamic range
capability is achieved by the combination of TDI CCD with gradient neutral density filter (NDF). On the basis of the
analysis and trade-off of system design, the prototype of novel visible nephograph for polar orbit platform is developed.
The results of experiments and tests in ground demonstration are satisfying, and the nephograph prototype is mainly met
the customer demand. In the end of paper, several problems and theirs solution of novel technology for space application
are also mentioned.
FY-2C is geostationary satellite which is researched and developed by China. The primary advantage of geostationary satellite is the ability to characterize the radiance by obtaining numerous views of a specific earth location at any time of a day. This allows the production of a composite image to monitor short-term weather better. This paper describes a technique that uses multi-spectral infrared composite images of FY-2C to estimate particles emission and recognize fog at night. Radiations of particles detected by FY-2C at different wavelengths are analyzed combined with solar spectral irradiance. Having several spectral bands makes the analysis algorithms more complex and inefficient, thus it is important to choose the most respective bands. By applying Karhunen-Loeve transform to raw data of FY-2C, the infrared images are analyzed. By comparing Eigen image of these infrared images with visible image in the same batch, it is concluded that data of IR3 contribute to the first Eigen image mostly, which shows that the newly added IR3 channel of FY-2C has greatly improved the ability of distinguishing short time weather phenomena. Producing composite images by calculation and analysis at sequential period of time can clearly show changes of fog coverage. The improvement of the geostationary satellite instruments that have come to pass will encourage more widespread use of these derived products in the coming years.
One of the bases of remote-sensing on water quality is to analyze reflectance just beneath water surface (0<sup>-</sup> deepness).
Because reflectance just beneath water surface can not be obtained directly, and remote sensing reflectance which is ratio
between water-leaving radiance and total radiance on water surface from sky can be obtained by spectroradiometer,
remote sensing reflectance is used commonly for building remote sensing model instead of reflectance just beneath water
surface. However, the water-leaving radiance obtained from the water surface includes some mirror reflections of the
water surface which reflect little information of the waterbodies. What's more, since the mirror reflections of the same
water surface are fluctuating when repeating the measurements in the same area of the water surface, the water-leaving
radiances obtained from this water surface are not identical in these measurements. Obviously, there is significant
difference between remote sensing reflectance and reflectance just beneath water surface. The remote-sensing model of
the waterbodies based on remote sensing reflectance exists some errors in retrieving the water quality. Therefore, it is
necessary to extracting reflectance just beneath water surface from measured remote sensing reflectance when building
the remote-sensing model of the waterbodies and retrieving the parameters of the water quality. This paper builds a novel
remote-sensing model and proposes an approach to extracting reflectance just beneath water surface from measured
remote sensing reflectance based on the model. In the proposed model, there are two assumptions: the radiance from the
underwater is steady and identical in all directions after the radiance entering into the under water is scattered entirely by
the water molecule and the particle of other material in the waterbodies, and the measurements of the radiance are
completed in a short period of time. Based on the above assumption, the differences among several remote sensing
reflectance which were measured repeatedly in same area of the waterbodies in a short time are related to fluctuation of
the water surface. In this model, the mirror reflectance model of water surface about wavelength is firstly obtained from
a group of remote sensing reflectance spectra measured repeatedly over same area of waterbodies, and then reflectance
just beneath water surface is extracted from the remote sensing reflectance using the least squared method and the
Levenberg -Marquardt algorithm. After the proposed model being built, three groups of experiments for remote sensing
reflectance measured above clean waterbodies, waterbodies with suspended sand and alga in Lake Taihu are conducted
and reflectance just beneath water surface of these three waterbodies are extracted successfully. Both the theoretical
deduction and the experimental result demonstrate that the proposed model is effective and efficient.