A high-performance lossy compression algorithm was proposed for remote sensing image compression based on bit allocation using sub-bands entropy.After decomposing the remote sensing image by using wavelet lifting scheme,the distribution of energy percentage and entropy of high frequency sub-bands were analyzed.A novel bit allocation method using the entropy was proposed.Uniform scalar quantification was implemented for each high frequency sub-band.Bit plane encoding followed and included two parts.The coordinates of non-zero coefficients were registered in the most significant bit plane,and run-length encoding and Huffman encoding were adopted for other bit planes.Experimental results show that the compression scheme performs well on a set of test remote sensing images including complicated texture images and relative planar ones.The Peak Signal to Noise Ratio (PSNR) is all higher than 34dB.However,the Compression Ratio (CR) depends on image’s complicated degree.