Structural similarity (SSIM) is an image quality assessment algorithm with the advantage of simplicity

high efficiency and better consistency with human subjectivity. However

it often fails when measuring badly distorted or cross distortion images. In this paper

an improved algorithm called structural similarity highlighting edge regions (HESSIM) is proposed based on the idea that edges are the most important information in an image.The humans eye is very sensible for distorted edge information. In the proposed HESSIM

the edge regions are first divided from an image by Otsu’s method

then those with obviously perceptual distortion are chosen by the JND model

and their distortion measures are highlighted. Experimental results show that HESSIM is more consistent with HVS than SSIM

especially for distorted images which are blurred or comtaminated with white noise.