摘要
结构相似性理论是一种关于图像质量评价的新思想,它很好地模拟了人眼视觉特性的整体功能。本文首先介绍了传统图像质量评价方法的不足,分析了基于视觉特性的结构相似度理论。作为结构相似性理论的一个实现,结构相似度模型(SSIM)简单且评价性能优于峰值信噪比(PSNR)或均方误差(MSE),但SSIM模型不能较好地评价严重模糊的降质图像。基于此,在SSIM基础上,本文提出了一种新颖的、基于边缘的图像质量评价模型(ESSIM)。该模型充分考虑了图像的边缘信息和人类视觉系统的关系。实验结果表明,ESSIM是一种有效的图像质量评价方法,尤其在对模糊图像的质量评价上优于结构相似度的评价方法SSIM。
The philosophy of structural similarity is a new idea about image quality assessment, which models the low level composition of Human Visual Systems（HVS）. The paper introduces the shortcomings of the traditional image quality assessment methods firstly,and analyzes the structural similarity theory based the human visual systems. As an implementation of the new philosophy, the Structural Similarity model（SSIM） is simple and has been proved to be better than the PSNR （Peak Signal to Noise Ratio） or the MSE （Mean Square Error）model, but there still remain some deficiencies in assessing badly blurred images. On the foundation of SSIM,the paper proposes a new image quality assessment method based on the Edge Structural Similarity（ESSIM）. It makes use of the relationship between the edge of image and the human visual system. The experimental results show that the ESSIM model is an effective method, and more consistent than the SSIM model.
出处
《计算机工程与科学》
CSCD
北大核心
2011年第2期133-136,共4页
Computer Engineering & Science
基金
国家自然科学基金资助项目(60573114)
山东省教育厅科技计划项目(J07YJ10)
关键词
图像质量评价
结构相似度
图像边缘
人眼视觉特性
image quality assessment
structural similarity
image edge
human visual system
