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.