The philosophy of structural similarity is a new idea about image quality assessment.Different from the traditional paradigm which modeling the low level composition of Human Visual System (HVS) bottom-up

the new philosophy modes the functionality of the overall HVS from top to down.As an implementation of the new philosophy

the Structural SIMilarity (SSIM) index is simple and efficient.However

SSIM fails in measuring the badly distorted images and images with cross distortion types.In this paper

we interpret the structural information as the mid and high frequencies with enough energy

and regard the SSIM index as a better distortion measure of local areas.Then

a new image quality index based on Structural Information Extraction (SIExt) is proposed.In SIExt

structural information is separated from image and given higher weight

and SSIM is used as an error measure to estimate local distortions.Experimental results show that the proposed SIExt can assess the quality of images more accurate than PSNR and SSIM.