Yang Chun-ling, Gao Wen-rui, Cao Duan-wu. Still Image Compression Algorithm Based on Structural Information Optimization[J]. Journal of Electronics & Information Technology, 2010, 32(7): 1574-1579. doi: 10.3724/SP.J.1146.2009.00983
Citation:
Yang Chun-ling, Gao Wen-rui, Cao Duan-wu. Still Image Compression Algorithm Based on Structural Information Optimization[J]. Journal of Electronics & Information Technology, 2010, 32(7): 1574-1579. doi: 10.3724/SP.J.1146.2009.00983
Yang Chun-ling, Gao Wen-rui, Cao Duan-wu. Still Image Compression Algorithm Based on Structural Information Optimization[J]. Journal of Electronics & Information Technology, 2010, 32(7): 1574-1579. doi: 10.3724/SP.J.1146.2009.00983
Citation:
Yang Chun-ling, Gao Wen-rui, Cao Duan-wu. Still Image Compression Algorithm Based on Structural Information Optimization[J]. Journal of Electronics & Information Technology, 2010, 32(7): 1574-1579. doi: 10.3724/SP.J.1146.2009.00983
JPEG2000 is a new still image compression standard based on wavelet transform. Compared with previous compression standards, it has a lot of advantages. However, in JPEG2000 the image distortion evaluation criteria is MSE, and MSE can not correlate very well with subjective ratings. So compression performance of JPEG2000 is affected greatly. In this paper, a still image compression algorithm SJPEG2000 that uses SSIM (Structural SIMilarity) as the distortion evaluation criteria is proposed under the framework of JPEG2000 standard. In order to let the compressed images retain more structural information, the algorithm intercept stream according to the contribution of the image structural information. Experimental results show that the images compressed by this algorithm retain much more structural information than original JPEG2000 and the corresponding SSIM value is also improved.