An Improved Image Quality Assessment Method Based on Structural Similarity

SSIM is an image quality assessment algorithm with the advantage of simplicity,high efficiency and better consistence. Its evaluation of performance is better than PNSR and MSE,however,it often fails when assessing badly distorted or cross distorted images. In this paper,an improved image quality assessment algorithm based on structural similarity( HSSIM) is proposed,which takes the histogram concentration as the main structural information of an image,according to the human visual characteristics,using histogram concentration to calculate the fuzzy degree of the image,obtaining the structure similarity value of the image finally. Experimental results show that,compared with the SSIM model,the proposed HSSIM model is more consistent with human visual system and can assess the quality of fault images more precisely.