摘要
基于结构信息的图像质量评价方法——结构相似度(SSIM)方法计算简单、性能优越,但该方法仅简单地将各子块SSIM的平均值作为整幅图像的平均结构相似度(MSSIM),而人眼对图像不同区域的视觉灵敏度不同.为此,文中提出了一种基于图像块分类的加权平均结构相似度(WSSIM)的图像质量评价方法,即先将图像分块并将子块区分成边缘块、细节块和平滑块三类,然后对不同类型块的SSIM值赋予不同的权值,最后计算得到整幅图像的WSSIM.实验结果证明,文中方法明显优于MSSIM和基于方差加权的SSIM.
Although the Structural Similarity （SSIM） method, a structural information-based method for image quality assessment, performs well with low computational complexity, it is still of some disadvantages because it simply takes the average SSIM of sub-blocks as the mean SSIM （MSSIM） of the whole image without considering the difference of human visual sensitivity in different image areas. In order to solve this problem, this palper proposes a block classification-based image quality assessment method named Weighted Structural Similarity （WSSIM）. In this method, an image is separated into some blocks that are further divided into edge blocks, detail blocks and smooth blocks, and the SSIMs of different types of blocks are weighted with different values to calculate the WSSIM of the whole image. Experimental results indicate that the proposed method is superior to the MSSIM method and the variance-based weighted SSIM.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2009年第1期42-47,共6页
Journal of South China University of Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(60402015)
广东省自然科学基金资助项目(06025642)
关键词
图像质量
评价
结构相似度
块分类
加权平均
人眼视觉系统
image quality
assessment
structural similarity
block classification
weighted average
human visual system
