Remote sensing imaging is disturbed by clouds frequently and produces images with low contrast and poor resolution. Algorithms removing clouds from single remote sensing images are expected to improve their qualities and aroused worldwide interests. Compared with multi-image methods, cloud removal algorithms from single images reduce the demands for weather and improve the image collecting flexibility. In this paper, a human-computer interactive system for cloud removal from single images was developed according to the proposed cloud removal algorithm. Firstly, the distributions of clouds and sceneries in the contaminated remote sensing images were discussed. Features of the dual tree complex wavelet transform (DTCWT) to split image frequencies were investigated after the principle of DTCWT was analyzed. By combining the frequency features of DTCWT sub-bands and the frequency distributions of the remote sensing images, the cloud removal algorithm based on DTCWT was proposed, and its procedures were described completed. Then, a human-computer interactive system for cloud removal was developed in order to improve the cloud removal processing conveniences and achieve the best performance. The development schemes were introduced. The system structures were illustrated. The design methods of the camera driver and video signal output program were described. Communication streams between modules and human-computer interaction interfaces were designed further according to the cloud removal algorithm based on DTCWT. The system has a very good flexibility which permits the input of most parameters from users and is expect to achieve a best performance. Finally, the device of the system was completed and tested. Image acquisition and cloud removal processing experiments were implemented by applying the human-computer interactive system. Cloud removal effects by adjusting parameters through the human-computer interaction interfaces were compared and evaluated. It proved that the designed system has a pleasant human-computer interaction ability and satisfactory cloud removal performance.
To obtain maximum possible details from source imagery, we propose a fast and effective image fusion method with guided saliency(IFGS). Our method first computes the saliency maps of all source images, and then each guided saliency map is generated using Logarithmic spectrum with an adaptive threshold value. Next, the weight of each component is computed by the guided gradient (FGG) method. Finally, the coefficients of the fused image are obtained by linearly combining the weights of the source images with the coefficients of the corresponding images. Experimental results demonstrate that our method can generate high-quality fusion images with better color and more details from multi-focus and multi-exposure compared to other fusion methods.
Modern industrial production technology is developing rapidly in recent decades. More and more traditional manual productions are becoming automatic when new automatic technologies are introduced among which machine vision plays an indispensable role. Aiming at the unmanned automatic production line of special steel castings in Shanghai MengTeng automatic technology co., LTD , in this paper an algorithm to recognize and position the special steel castings autonomously is proposed based on the binocular vision theory. The technologies including the pyramid hierarchical matching and the deep neural network are described in detain. The identification and positioning of special steel castings is realized. Its procedures are described completed. Some experiments are implemented by using manipulator to grasp the steel castings and running the proposed algorithm. It proves that the proposed algorithm achieves satisfactory results.
Star sensors achieve very accurate attitudes for space vehicles by comparing observed stars in their field of view with the cataloged guide stars. Guide star selection is a key work during the star sensor designing. Infrared star sensor provides accuracy navigation information to air vehicles which fly near the ground in the atmosphere. According to working characteristics of the infrared star sensors, 2MASS(Two Micron All Sky Survey) star catalog is adopted as the raw star source. On the basis of analyzing its data structure, the scheme of selecting binary stars as guide stars and calculating their equivalent magnitudes and positions is discussed. The procedures to select the guide stars are described completely by processing 2MASS. The guide star catalog for infrared star sensors is established. The result proves that guide stars in the near infrared band are far more than those in the visible band in case of the same limiting magnitude. Star camera of infrared star sensors can adopt systems having smaller aperture or narrower field of view.
Sparse aperture optical system is arranged by a number of small apertures or reflective optical systems according to certain rules. It reduces the processing difficulty, the weight and the cost of the telescope system while its resolution is equivalent to that of a single-aperture telescope system. In this paper, the Cassegrain telescope system with three sub-mirror sparse aperture primary mirror as the spherical surface is used as the initial structure and optimized. The freeform surface is introduced into the sparse aperture optical system to increase the freedoms of optical design, balance aberrations and improve the imaging quality. On this basis, the three sub-mirror sparse aperture with freeform surface is designed and its image quality is analyzed.
To prevent halo artifacts resulting from edge preserving smoothing methods that use a local filter, a filter method with a guided image that fuses multiple kernels is proposed. This method first computes the coefficients of different local multiple kernels at the pixel level and then linearly fuses these coefficients to obtain the final coefficients. Finally, the filtered image is generated using the linear coefficients. Compared with existing methods, including the popular bilateral filter and guided filter methods, our experimental results show that the proposed method not only obtains images with better visual quality but also prevents halo artifacts, resulting in detail enhancement, haze removal, and noise reduction.
Modern space telescopes are demanded to have a very large aperture in order to achieve high resolution. The notion of
the sparse aperture systems introduces a new solution to make the telescopes practicable. It is significant to simulate
sparse aperture systems before their application in space observation. The multiple mirror telescope (MMT) is one type
of sparse aperture systems and Golay3 is the configuration serving as a good start. The method to simulate Golay3 MMT
is investigated. The fundamental principle of optical surfaces simulation using the optical design program is discussed. It
is proposed that Golay3 MMT simulation can be accomplished by programming to establish surface files with the aid of
the interface of this program. The structure of Golay3 MMT in which three sub-mirrors replace the monolithic spherical
primary mirror is analyzed. The formulas determining locations of sub-mirrors on the spherical primary mirror are
deduced. The surface file representing the primary mirror is created by external programming and defining properties of
rays passing through it. The simulation procedures are introduced in detail. A simulation example is given out and
evaluated. It proves that the simulation method is reasonable and effective, and has significant reference values to
simulate sparse aperture systems with other structures.
Modern star sensors are powerful to measure attitude automatically which assure a perfect performance of spacecrafts.
They achieve very accurate attitudes by applying algorithms to process star maps obtained by the star camera mounted
on them. Therefore, star maps play an important role in designing star cameras and developing procession algorithms.
Furthermore, star maps supply significant supports to exam the performance of star sensors completely before their
launch. However, it is not always convenient to supply abundant star maps by taking pictures of the sky. Thus, star map
simulation with the aid of computer attracts a lot of interests by virtue of its low price and good convenience. A method
to simulate star maps by programming and extending the function of the optical design program ZEMAX is proposed.
The star map simulation system is established. Firstly, based on analyzing the working procedures of star sensors to
measure attitudes and the basic method to design optical system by ZEMAX, the principle of simulating star sensor
imaging is given out in detail. The theory about adding false stars and noises, and outputting maps is discussed and the
corresponding approaches are proposed. Then, by external programming, the star map simulation program is designed
and produced. Its user interference and operation are introduced. Applications of star map simulation method in
evaluating optical system, star image extraction algorithm and star identification algorithm, and calibrating system errors
are presented completely. It was proved that the proposed simulation method provides magnificent supports to the study
on star sensors, and improves the performance of star sensors efficiently.
Star sensors have been developed to acquire accurate orientation information in recent decades superior to other attitude
measuring instruments. A star camera takes photos of the night sky to obtain star maps. An important step to acquire
attitude knowledge is to compare the features of the observed stars in the maps with those of the cataloged stars using
star identification algorithms. To calculate centroids of the star images before this step, they are required to be extracted
from the star maps in advance. However, some large or ultra large imaging detectors are applied to acquire star maps for
star sensors with the development of electronic imaging devices. Therefore, star image extraction occupies more and
more portions of the whole attitude measurement period of time. It is required to shorten star image extraction time in
order to achieve higher response rate. In this paper, a novel star image extraction algorithm is proposed which fulfill the
tasks efficiently. By scanning star map, the pixels brighter than the gray threshold are found and their coordinates and
brightness are stored in a cross-linked list. Data of these pixels are linked by pointers, while other pixels are neglected.
Therefore, region growing algorithm can be used by choosing the first element in the list as a starting seed. New seeds
are founded if the neighboring pixels are brighter than the threshold, and the last seed is deleted from the list. Next
search continues until no neighboring pixels are in the list. At that time, one star image is extracted, and its centroid is
calculated. Likely, other star images may be extracted, and then the examined seeds are deleted which are never
considered again. A new star image search always begins from the first element for avoiding unnecessary scanning. The
experiments have proved that for a 1024×1024 star map, the image extraction takes nearly 16 milliseconds. When
CMOS APS is utilized to transfer image data, the real-time extraction can be almost achieved.
Star camera is a kind of sensitive attitude sensors used for navigation of space vehicles. In order to use it on aircrafts in
daytime, the conceptual design and the principle of airborne daytime infrared star cameras are introduced in this paper, as
there is enough number of stars in near infrared band to be used as reference of a star camera for calculating attitude.
Through analyzing the atmospheric scattering background light intensity for different altitudes, observing angles, and
solar angles with Modtran software, and considering IR FPA (infrared focal plane array) performance, shot noise and the
required star magnitude for daytime star trackers and sensors, the optical system parameters, i.e. FOV (field of view),
clear aperture diameter and effective focal length, are determined according to the required SNR (signal to noise ratio).
The modern spacecrafts harassed by the "lost-in-space" problem frequently desire for retrieving their orientations
autonomously while performing missions especially in deep space. Star sensor becomes a preferred assistant which
determines the attitudes with very high accuracy. Autonomous APS star sensors have been the development trends in
virtue of their lighter weight, smaller size, less power, and the ability to acquire attitude knowledge autonomously. By
analyzing the principle of attitude measurement applying star identification algorithm, the requirements for the
aberration correction and imaging quality of their optical systems are discussed. The statistics of star numbers in
different orientations is analyzed making use of guide star catalogs established with various limiting star magnitudes and
fields of view (FOV). The method to determine parameters of the optical system including aperture size, FOV, focal
length and spectrum range is introduced. These parameters meeting the demand of the Pyramid identification algorithm
utilized in this paper to realize the autonomous attitude reorganization in any orientations are calculated. Accordingly, a
star camera is designed with STAR 1000 APS as its detector. Its focal length, aperture diameter and circular field of view
are 43.56mm, 27.3mm and 20 degrees, respectively. Structure selection and aberration correction schemes are presented.
Aberrations including coma, astigmatism, and distortion and lateral color are corrected, and spherical aberration and
longitudinal color are controlled. This camera is telecentric in the image field which assures that the star identification is
still valid even though the image plane suffers from a deviation as a result of the environmental alteration and
Star trackers determine attitude by identifying stars imaged on the image sensor via an optical system whose
performance is required to meet the star identification algorithm. The method to determine parameters of the optical
system is proposed based on the identification algorithm. These parameters include focal length, aperture, and field of
view (FOV). Aberration correction requirements are also analyzed. Pyramid identification algorithm utilized in this
paper is investigated. Some improved approaches are presented for star map processing, onboard catalog organization
and star identification. A link table construction is designed to save brightness from the programmed APS sensor which
decreases data effectively and enhances the ability to calculate star positions in star maps. A method is developed to
organize the onboard catalog which avoids searching and comparing similar star pairs but makes for rapid and unique
identification. When performing star identification with Pyramid identification algorithm, only X brightest stars are
chosen from star maps to acquire high signal to noise ratio and decrease spikes. Star number statistics is fulfilled all over
the sky with any orientations by varying FOV and limited magnitude. Base on the requirement of the identification
algorithm, parameters of the optical system are determined with the given STAR1000 APS sensor by analyzing their
feasibility in optical design. According to these determined parameters, a star camera is designed. An onboard catalog on
which star identification relies is produced. Star identification simulation is implemented. Simulation result proves that
the designed system gets a satisfactory performance.
By analyzing the multi-resolution characteristics of wavelet series, the frequency distribution of detail and approximation
coefficients is deduced. It is concluded that the frequency of detail coefficients in low levels is higher than that in high
levels, and the frequency of approximation coefficients is the lowest. According to this conclusion, this paper proposes a
new method of remote sensing image recovery based on Weighted Wavelet Coefficient (WWC), namely, removing the
cloud and mist from the remote sensing images using weighted wavelet coefficient algorithm. Suppose the image is
decomposed by η levels with wavelet transform. By choosing reasonable level number l, the scenery information is
mainly distributed to 1~l levels where detail coefficients have lower frequency and cloud and mist noise information are
distributed mainly to l~n; levels where detail coefficients have relatively higher frequency. Approximation coefficients
will also include cloud information. Detail coefficients in low levels and high levels and approximation coefficients are
weighted with different factors. The scenery information is enhanced by increasing detail coefficients in low levels with
a weight great than 1. The cloud and mist noise is weakened by decreasing detail coefficients in high levels with a weight
less than 1. Approximation coefficients are weighted appropriately if including cloud. It is also proposed that the
information entropy is taken as a criterion for choosing the number of the demarcation levels and the weighted factors.
We have confirmed that our new algorithm is better than homomorphism filtering and Retinex algorithm by experiments.
Sparse aperture telescopes represent a promising technology for increasing the effective diameter of an optical system
while reducing the weight and the size. Multiple-mirror telescope (MMT) and multiple-telescope telescope (MTT) are
two types of sparse aperture systems. The primary mirror of MMT consists of a number of segments that are all parts of a
single primary-mirror conic. The configuration of the sparse aperture is related to the performance of the MMT. Golay
configuration is nonredundant sparse aperture. Entrance pupil characteristics of Golay 6 MMT are studied to research the
relationships between the sub-mirrors on the primary mirror and the shapes of sub-apertures on the entrance pupil of
Golay 6. Overlay factor and efficiency factor are proposed to achieve the optimal fill factor on the entrance pupil. Given
the relative aperture of Golay 6 MMT, there is some concern that the fill factor on the entrance pupil is larger than the
overlay fill factor on the spherical sparse aperture primary mirror. The maximum fill factor and the maximal overlay
factor are discussed, and the tangency condition when sub-mirrors of Golay 6 MMT are tangency is derived. Two
Cassegrain telescopes having a spherical primary mirror with Golay6 configuration and with an aspherical secondary
mirror are designed. The fill factor on the entrance pupil can be larger than the overlay factor on the primary mirror at the
certain occasion. Based on the relationships between the fill factor and the overlay factor, the rational parameters of
sub-mirrors on the primary mirror can be selected.
High resolution imaging from space telescope for surveillance and astrometry is currently limited by launch vehicles
and systems cost. The weight of the telescope is one of major factors which limits the vehicles to be placed in orbit.
Sparse aperture optical system uses a reduced aperture area to synthesize the optical performance of a filled aperture. It
is more promising in virtue of its light weight, low cost and larger synthetic aperture. The sparse aperture optical system
has two types, i.e. the multiple-mirror telescope (MMT) and the multiple-telescope telescope (MTT). A MMT of
Golay3 sparse aperture optical system is investigated that three sub-mirrors are located on a spherical primary mirror.
Three sub apertures of Golay3 are elliptic that in fact the circular sub-mirrors of spherical primary mirror are projected
on the entrance pupil. The relationships between fill factor, radius of sub-mirrors and F number of the primary mirror
are presented. The analytical formula is also completed, which shows that the maximum fill factor is limited by F
number of the primary mirror. When the aperture radius is equal to curvature radius of the primary mirror
approximately, the shape of sub-apertures exhibits to be elliptic obviously. The maximum fill factor reaches the largest
one at that time. Modulation Transfer Function (MTF) of Golay3 system is studied. MTF is the correlation of three
elliptic sub-apertures. The sub-MTFs are different from those of sub-mirrors located on a plane. The formula is verified
by designing two Cassegrain telescopes which primary mirror is made up of three sub-mirrors of Golay3 configuration
with Zemax optical program. Three sub-mirrors of primary mirror share a common asphercial secondary mirror. The
errors caused by tilt and piston of three sub-apertures are also given out. Because of the loss of MTF for the sparse
aperture optical system, the image quality is decreased. Wiener filter technique is utilized to improve the image quality
for the sparse aperture system.
This article proposes an effective method for removing the thin cloud and mist in the remote sensing images using Mallat algorithm by analyzing the frequency distribution characteristics of the remote sensing images influenced by cloud and mist. Based on the characteristics of relatively lower frequency of the cloud and fog, relatively higher frequency of the scenes, and the multi-resolution of the wavelet function, we analyze the characteristics of the wavelet transformation in both the theory and the practical application, and conclude that the detail coefficient at the lower level of the wavelet represents relatively high-frequency of the image, the detail coefficient at its higher level represents the relatively low frequency band of the image. Like this, we can effectively strengthen the high-frequency components and weaken the
low frequency components in the images, achieve goal for removing cloud and mist. The experimental results of the proposed algorithm are found to be satisfactory.