An Improved Algorithm for Image Quality Assessment

摘要：

The Structural Similarity model (SSIM) is a new idea about image quality assessment and has been proved to be more effective than the PSNR (Peak Signal to Noise Ratio) and the MSE (Mean Square Error) model. However,it has some deficiencies in distinguishing badly blurred images from noise adding ones. For this,a new image quality assessment method based on the Quadtree Structural Similarity (QUSSIM) which makes use of relationship between edge and non-edge part of an image is proposed in this paper. Experimental results show that the QUSSIM model is more consistent with the subjective mean opinion score (MOS) than the SSIM one.

关键词： image quality assessment SSIM quadtree QUSSIM

作者: Zhou Yuan-pu Yang Hua Yang Xing Hao Xiao-li Wang Yi-cheng Feng Yun-song Fan Bin

作者单位: State Key Laboratory of Pulsed Power Laser Technology,Hefei,230037,China Key Lab of Infrared and Low School of Electronics and Information Engineering,Beijing Jiaotong University Beijing,100044,China Military Representative office of Land Aviation Division of General Staff Department Based in Shangh

会议类型: 国际会议

会议名称: 2011 International Conference on Opto-Electronics Engineering and Information Science(2011光电电子工程与信息科学国际会议 ICOEIS 2011)

会议地点: 西安

会议语种:英文

页码: 2165-2167

在线出版日期: 2011-12-23（万方平台首次上网日期，不代表论文的发表时间）