结合HVS和相似性度量的图像质量评价测度

图像质量评价是图像处理领域内一项很有意义的研究课题。传统的评价方法(如PSNR和MSE)只是在像素域统计参考图像和失真图像的误差，因而不能有效反映图像的视觉感知质量。针对上述问题，在充分考虑人眼视觉感知特性的基础上，提出一种新颖的图像质量评价算法，通过模拟人类视觉系统，并结合相似性度量方法获得有效的图像质量评价测度。实验结果显示，采用本文方法获得的图像质量评价结果与主观感知具有较好的一致性，能准确地反映人眼对图像质量的视觉感知。

Image quality assessment metrics based on human visual system

Image quality assessment is important in the image processing field. The traditional methods (e.g. PSNR and MSE) only compute the error between the reference image and distorted image at the pixel-scale, so they cannot well reflect the visual quality of image. Aiming at the above problem, a novel image quality evaluation approach is proposed according to the human visual characteristics. It is obtained to mimic human visual system and utilize similarity measure methods. Experimental results illustrate that the proposed has a good consistency with the subjective assessment of human beings; thus it can be used to describe the visual perception of the image effectively.