Classified coset coding based lossless compression of hyperspectral images

Juan Song; Yunsong Li; Haiying Liu; Xianyun Wu; Keyan Wang

doi:10.1117/12.895426

16 September 2011 Classified coset coding based lossless compression of hyperspectral images

Juan Song, Yunsong Li, Haiying Liu, Xianyun Wu, Keyan Wang

Author Affiliations +

Proceedings Volume 8157, Satellite Data Compression, Communications, and Processing VII; 81570V (2011) https://doi.org/10.1117/12.895426
Event: SPIE Optical Engineering + Applications, 2011, San Diego, California, United States

Abstract

Due to the restrained resources on board, compression methods with low complexity are desirable for hyperspectral images. A low-complexity scalar coset coding based distributed compression method (s-DSC) has been proposed for hyperspectral images. However there still exists much redundancy since the bitrate of the block to be encoded is determined by its maximum prediction error. In this paper, a classified coset coding based lossless compression method is proposed to further reduce the bitrate. The current block is classified to make the pixels with similar spectral correlation cluster together. Then each class of pixels is coset coded respectively. The experimental results show that the classification could reduce the bitrate efficiently.

Citation Download Citation

Juan Song, Yunsong Li, Haiying Liu, Xianyun Wu, and Keyan Wang "Classified coset coding based lossless compression of hyperspectral images", Proc. SPIE 8157, Satellite Data Compression, Communications, and Processing VII, 81570V (16 September 2011); https://doi.org/10.1117/12.895426

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