Journal of Jilin University Science Edition
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MA Xinhong, GUO Shuxu
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In order to improve sampling of the compression coding technology and constantly improve the imaging spectrometer systems, based on the principles of the sparse decomposition and compressed sensing, hyperspectral remote sensing images were compressed and reconstructed. A fast sparse decomposition algorithm of the image decomposition on over\|complete atomic library was proposed so as to reduce the amount of computing. The simulation results show that the calculation improved processing speed and reduced costs by spectral compression of hyperspectral images carried out with the compressed sensing and bands grouping technology.
Key words: sparse decomposition, compressed sensing (CS), hyperspectral remote sensing images, Gabor atomic greedy clustering algorithm (GAGCA)
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MA Xinhong, GUO Shuxu. Compressed Sensing and Sparse Decomposition ofHyperspectral Remote Sensing Images[J].Journal of Jilin University Science Edition, 2015, 53(04): 767-772.
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http://xuebao.jlu.edu.cn/lxb/EN/Y2015/V53/I04/767
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