【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.更多还原

【Abstract】 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 paper 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.更多还原