A New Interference Multispectral Image Compression Method Applied to Deep Space Reconnaissance(Remote sensing/Radar (1), Workshop for Space, Aeronautical and Navigational Electronics (W S A N E 2005))
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概要
- 論文の詳細を見る
Interference multispectral images have got more attention recently in the imaging remote sensing for the deep space reconnaissance. To get more effective image transmission between the explorer and the earth, and the explorers, it is necessary to study the methods of higher compression ratio with good enough fidelity for the images. China is planning to launch a moon orbiter in a few year and the interference multispectral images are the important data source in the remote sensing system of the orbiter. A new compression method for interference multispectral remote sensing images is presented in the paper. A new rectangle region-of-interest (ROI) compression algorithm is integrated with an embedded-block-coding optimized truncation (EBCOT) method to make a distortion tracking of the spectral region. A rate-distortion optimizer is also designed to give an adaptive lifting of the rate-distortion slopes. The higher peak signal to noise ratio (PSNR) for the reconstructed multispectral images can be obtained by adopting the method. In the method, the lifting procedure is carried out in a code stream organization stage. The coarse liftingstep situation due to the nature of bitplane shift methods can be improved, which enables flexible adjustment of compression fidelity in the ROI and background (BG), and improves the quality of the BG and the whole image. The experimental results for a set of multispectral images show that the method is very efficient.
- 社団法人電子情報通信学会の論文
- 2005-02-25
著者
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YANG Hong
Department of Pathology, Xuanwu Hospital, Capital University of Medical Sciences
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Xiao Jiang
Department Of Information Engineering Xidian University
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Yang Hong
Department Of Information Engineering Xidian University
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Wu Chengke
Department Of Information Engineering Xidian University
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Li Yunsong
Department Of Information Engineering Xidian University
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Yang Hong
Department Of Chemistry North Carolina State University
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