Algorithm for satellite remote sensing image compression with adaptive quantization based on global restrictions

To deal with the redundant computation in JPEG2000 which affects the compression speed of satellite remote sensing image. An algorithm for fast compression of satellite remote sensing image with adaptive quantization based on global restrictions (AQGR) is proposed. According to the target bit rate, the input image and the characteristics of subbands, the subband quantization step is set up adaptively from the overall perspective with consideration of inner relationship in the processes of JPEG2000 witch reduces redundant data which are the most time-consuming to be encoded in EBCOT. Experimental results show that compared with Jasper, AQGR reduces 90%-95% redundant data, thereby reduces the encoding time in Tile1 and truncation time in Tile2, and significantly improves the coding speed of JPEG2000. Furthermore, the peak signal-to-noise ratio (PSNR) of the reconstructed image is increased slightly.