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基于梯度的结构相似度的图像质量评价方法
引用本文:杨春玲,旷开智,陈冠豪,谢胜利. 基于梯度的结构相似度的图像质量评价方法[J]. 华南理工大学学报(自然科学版), 2006, 34(9): 22-25
作者姓名:杨春玲  旷开智  陈冠豪  谢胜利
作者单位:华南理工大学,电子与信息学院,广东,广州,510640
基金项目:国家自然科学基金;国家自然科学基金
摘    要:虽然基于结构信息的图像质量评价方法——结构相似度(SSIM)模型结构简单、评价性能优于峰值信噪比(PSNR)或均方误差(MSE)模型,但SSIM模型不能较好地评价严重模糊的降质图像.文中提出了一种基于梯度的结构相似度(GSSIM)图像质量评价方法,该方法将梯度作为图像的主要结构信息.实验结果表明,GSSIM模型比SSIM和PSNR(MSE)模型更符合人眼视觉系统特性,能较好地评价模糊图像的质量.

关 键 词:图像质量  评价  结构相似度  基于梯度的结构相似度  人眼视觉系统
文章编号:1000-565X(2006)09-0022-04
收稿时间:2005-11-21
修稿时间:2005-11-21

Gradient-Based Structural Similarity for Image Quality Assessment
Yang Chun-ling,Kuang Kai-zhi,Chen Guan-hao,Xie Sheng-li. Gradient-Based Structural Similarity for Image Quality Assessment[J]. Journal of South China University of Technology(Natural Science Edition), 2006, 34(9): 22-25
Authors:Yang Chun-ling  Kuang Kai-zhi  Chen Guan-hao  Xie Sheng-li
Affiliation:School of Electronic and Information Engineering, South China Univ. of Tech. , Guangzhou 510640, Guangdong, China
Abstract:Although the SSIM(Structural Similarity) model,an assessment model of image quality based on the structural information,has been proved to be better than the PSNR(Peak Signal to Noise Ratio) or the MSE(Mean Square Error) model,there still remain some deficiencies in assessing badly blurred images.In order to solve this problem,this paper proposes a gradient-based structural similarity(GSSIM) model that takes the gradient as the main structural information of an image.Experimental results show that the proposed GSSIM model is more consistent with human visual system and can assess the quality of blurred images more precisely than the SSIM and PSNR(MSE) models.
Keywords:image quality    assessment    structural similarity    gradient-based structural similarity    human visual system
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