Remote Sensing Image Compression Algorithm Based on Wavelet Sub-bands Entropy

摘要

A high-performance lossy compression algorithm was proposed for remote sensing image compression, which was based on bit allocation using sub-bands entropy. After decomposing the remote sensing image using maximum lifting scheme of morphological Harr wavelet, the distribution of energy percentage and entropy of high frequency sub-bands was analyzed. A novel bit allocation method using the entropy was proposed. Non-uniform scalar quantification was implemented for each high frequency sub-band. Bit plane encoding follows and includes two parts. The coordinates of non-zero coefficients were registered in the most significant bit plane, and run-length encoding and Huffman encoding were proceeded for other bit planes. Experimental results show that the compression scheme performs well on a set of test remote sensing images. The peak signal to noise ratio (PSNR) is all higher than 34dB, however, the compression ratio (CR) depends on image's complicated degree.