Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and processing capacity, are limited. For multispectral images, the compression algorithms based on 3D transform (like 3D DWT, 3D DCT) are too complex to be implemented in space mission. In this paper, we proposed a compression algorithm based on distributed source coding (DSC) combined with image data compression (IDC) approach recommended by CCSDS for multispectral images, which has low complexity, high robust, and high performance. First, each band is sparsely represented by DWT to obtain wavelet coefficients. Then, the wavelet coefficients are encoded by bit plane encoder (BPE). Finally, the BPE is merged to the DSC strategy of Slepian-Wolf (SW) based on QC-LDPC by deep coupling way to remove the residual redundancy between the adjacent bands. A series of multispectral images is used to test our algorithm. Experimental results show that the proposed DSC combined with the CCSDS-IDC (DSC-CCSDS)-based algorithm has better compression performance than the traditional compression approaches.

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3d dwt 3d dct dsc strategy of slepianwolf sw image data compression idc approach distributed source coding dsc bit plane encoder residual redundancy ccsdsidc dscccsdsbased algorithm wavelet coefficients coupling multispectral images qcldpc bpe sensing

Jin Li,Fei Xing,Ting Sun,Zheng You,.Multispectral Image Compression Based on DSC Combined with CCSDS-IDC. 2014 (),.

Jin Li,Fei Xing,Ting Sun,Zheng You,"Multispectral Image Compression Based on DSC Combined with CCSDS-IDC" 2014

Jin Li,Fei Xing,Ting Sun,Zheng You,"Multispectral Image Compression Based on DSC Combined with CCSDS-IDC"