Classified coset coding based lossless compression of hyperspectral images

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.