Low-Complexity Compression Algorithm for Hyperspectral Images Based on Distributed Source Coding

被引：6
作者：
Nian, Yongjian [1 ]
He, Mi [2 ,3 ]
Wan, Jianwei [1 ]
机构：
[1] Natl Univ Def Technol, Coll Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China
[2] Third Mil Med Univ, Sch Biomed Engn, Chongqing 400038, Peoples R China
[3] Chongqing Univ, Chongqing 400038, Peoples R China
来源：
MATHEMATICAL PROBLEMS IN ENGINEERING | 2013年 / 2013卷
基金：
中国国家自然科学基金;
关键词：
LOSSLESS COMPRESSION; INFORMATION; TRANSFORM;
D O I：
10.1155/2013/825673
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
A low-complexity compression algorithm for hyperspectral images based on distributed source coding (DSC) is proposed in this paper. The proposed distributed compression algorithm can realize both lossless and lossy compression, which is implemented by performing scalar quantization strategy on the original hyperspectral images followed by distributed lossless compression. Multilinear regression model is introduced for distributed lossless compression in order to improve the quality of side information. Optimal quantized step is determined according to the restriction of the correct DSC decoding, which makes the proposed algorithm achieve near lossless compression. Moreover, an effective rate distortion algorithm is introduced for the proposed algorithm to achieve low bit rate. Experimental results show that the compression performance of the proposed algorithm is competitive with that of the state-of-the-art compression algorithms for hyperspectral images.
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收藏
页数：7
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