基于Curvelet变换的图像质量多尺度灰评价  

Multi-scales grey evaluation on images quality based on Curvelet transform

作　　者：马苗[1] 胡菁超[1] 

机构地区：[1]陕西师范大学计算机科学学院,西安710062

出　　处：《计算机工程与应用》2010年第29期179-182,191,共5页Computer Engineering and Applications

基　　金：国家自然科学基金(No.60803088;No.10974130);陕西省自然科学基金(No.2007D07;No.2009JM8018);中央高校基本科研业务费专项资金重点项目(No.GK200901006)~~

摘　　要：为了更加客观有效地评价图像质量,利用灰色关联分析理论的整体比较机制和Curvelet变换多尺度多方向分析图像特征的优点,提出一种改进的图像质量评价算法——Curvelet系数灰关联法。该算法首先在不同尺度和不同方向上得到待评价图像与参考图像之间的灰色关联度,然后对同一尺度上各个方向的关联度求均值,利用其与标准参考序列进行二次关联比较,从而从二个层次综合评价图像质量。实验表明,该方法不仅能够提供更多的质量信息,而且较PSNR评价方法,能够更好地符合人眼的主观感知。In order to evaluate image quality efficiently and objectively,this paper proposes a Curvelet transform and grey relation analysis based method which utilizes the global comparison mechanism of grey relational analysis theory and the analysis ability in multi-scales and multi-direction of Curvelet transform.Firstly, the grey relational grades between evaluating images and the reference image at different scales and directions are gained.Secondly,the mean of the relational grades at all angles in the same scale is computed, and then, a global relational grade between the mean and the reference sequence is produced which provides us with an image quality in two levels.Experimental results show that the new method not only may estimate image quality at different scales and angles,but also produces more reasonable conclusions than PSNR based methods.

关 键 词：图像质量 CURVELET变换 灰色关联度 人类视觉系统 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] N941.5[自动化与计算机技术—计算机科学与技术]