作者:
吴伟仁田玉龙黄翔宇Institute for Pattern Recognition and Artificial Intelligence
State Key Lab. for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China Deep Space Exploration Research Center
Harbin Institute of Technology Harbin 150001 Chinahe image elements of earth-center and moon-center are obtained by processing the images of earth and moon these image elements in combination with the inertial attitude information and the moon ephemeris are utilized to obtain the probe initial position relative to earth and the Levenberg-Marquardt algorithm is used to determine the accurate probe position relative to earth and the probe orbit relative to earth is estimated by using the extended Kalman filter. The autonomous optical navigation algorithm is validated using the digital simulation.
The image elements of earth-center and moon-center are obtained by processing the images of earthand moon, these image elements in combination with the inertial attitude information and the moon ephemerisare utilized ...
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The image elements of earth-center and moon-center are obtained by processing the images of earthand moon, these image elements in combination with the inertial attitude information and the moon ephemerisare utilized to obtain the probe initial position relative to earth, and the Levenberg-Marquardt algorithm is usedto determine the accurate probe position relative to earth, and the probe orbit relative to earth is estimated by u-sing the extended Kalman filter. The autonomous optical navigation algorithm is validated using the digital simu-lation.
A new approach for the personal identification using hand images is presented. This paper attempts to improve the performance of palmprint-based verification system by integrating hand geometry features. Unlike other ...
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This paper presents improvements in generation of wideband and high dynamic range analog signal for area-efficient MADBIST, especially for the on-chip testing of wireless communication IF digitizing sigma-delta modula...
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作者:
王振华吴伟仁田玉龙田金文柳健Institute for Pattern Recognition and Artificial Intelligence
State Key Lab for Image Processing and Intelligent ControlHuazhong University of Science and Technology Wuhan 430074 China Institute for Pattern Recognition and Artificial Intelligence
State Key Lab for Image Processing and Intelligent ControlHuazhong University of Science and Technology Wuhan 430074 China major limitation for deep space communication is the limited bandwidths available. The downlink rate using X-band with an L2 halo orbit is estimated to be of only 5.35 GB/d. However the Next Generation Space Telescope (NGST) will produce about 600 GB/d. Clearly the volume of data to downlink must be reduced by at least a factor of 100. One of the resolutions is to encode the data using very low bit rate image compression techniques. An very low bit rate image compression method based on region of interest(ROI) has been proposed for deep space image. The conventional image compression algorithms which encode the original data without any data analysis can maintain very good details and haven't high compression rate while the modern image compressions with semantic organization can have high compression rate even to be hundred and can't maintain too much details. The algorithms based on region of interest inheriting from the two previews algorithms have good semantic features and high fidelity and is therefore suitable for applications at a low bit rate. The proposed method extracts the region of interest by texture analysis after wavelet transform and gains optimal local quality with bit rate control. The Result shows that our method can maintain more details in ROI than general image compression algorithm(SPIHT) under the condition of sacrificing the quality of other uninterested areas
A major limitation for deep space communication is the limited bandwidths availab.e. The downlinkrate using X-band with an L2 halo orbit is estimated to be of only 5.35 GB/d. However, the Next GenerationSpace Telescop...
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A major limitation for deep space communication is the limited bandwidths availab.e. The downlinkrate using X-band with an L2 halo orbit is estimated to be of only 5.35 GB/d. However, the Next GenerationSpace Telescope (NGST) will produce about 600 GB/d. Clearly the volume of data to downlink must be re-duced by at least a factor of 100. One of the resolutions is to encode the data using very low bit rate image com-pression techniques. An very low bit rate image compression method based on region of interest(ROI) has beenproposed for deep space image. The conventional image compression algorithms which encode the original datawithout any data analysis can maintain very good details and haven' t high compression rate while the modernimage compressions with semantic organization can have high compression rate even to be hundred and can' tmaintain too much details. The algorithms based on region of interest inheriting from the two previews algorithmshave good semantic features and high fidelity, and is therefore suitable for applications at a low bit rate. Theproposed method extracts the region of interest by texture analysis after wavelet transform and gains optimal localquality with bit rate control. The Result shows that our method can maintain more details in ROI than generalimage compression algorithm(SPIHT) under the condition of sacrificing the quality of other uninterested areas.
A FLIR image segmentation algorithm based on genetic algorithm and fuzzy set theory was presented. The method defines different member function for the object and background of the image to transform the image into fu...
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A FLIR image segmentation algorithm based on genetic algorithm and fuzzy set theory was presented. The method defines different member function for the object and background of the image to transform the image into fuzzy domain with maximum fuzzy entropy. The procedure for finding combination of a, b and c is implemented by genetic algorithm, thresholding image into object and background by maximizing the fuzzy entropy. The experiment results show that our proposed method gives better performance and higher calculation speed than other general methods with good real-time by using genetic algorithm.
With the development of remote sensing technique, onboard data compression has become an urgent need and a lot of study has been directed toward the development of efficient techniques. In this paper, the construction...
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This paper proposes a hybrid approach of texture-based method and connected component-based one for extracting texts in real scene images. For detecting texts having a lot of variations in size, shape, etc. we use a m...
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We propose a text scanner, which detects wide text strings in a sequence of scene images. For scene text detection, we use a multiple-CAMShift algorithm on a text probability image produced by a multi-layer perceptron...
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We propose a text scanner, which detects wide text strings in a sequence of scene images. For scene text detection, we use a multiple-CAMShift algorithm on a text probability image produced by a multi-layer perceptron...
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A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss func...
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