Hyperspectral Image Compression By Using Distributed Source Coding

This paper presents an efficient compression algorithm based on distributed source coding. The proposed algorithm employs a block-based quantizer followed by distributed lossless coding. First, a bit-rate allocation algorithm is used to assign the rational bit-rate for each block. Subsequently, the multi-linear regression model is employed to construct the side information of each block, and the optimal quantization step size of each block is obtained under the assigned bit-rate while minimizing the distortion. Finally, the quantized block is encoded by distributed lossless compression. Experimental results show that the proposed algorithm provides competitive compression performance, low encoder complexity and error resilience.