鉴于传统的图像质量评价测度，如峰值信噪比，不能有效地反映人对图像的视觉感知。为此，提出了一种基于内容的图像质量评价测度；在改进基于结构相似度（structural similarity，SSIM）的图像质量测度基础上，根据图像的内容将图像分成边缘、纹理和平滑区域3部分，在每个区域又利用模糊积分融入了结构相似性的数量信息，从而充分利用了图像结构信息相似性及其在位置和数量上的融合信息来全面评价图像质量。实验结果表明，利用该测度所得到的图像质量评价结果与主观评价结果有着很好的相关性，能较准确地反映人对图像质量的主观感受。

The traditional image quality evaluation metric, such as PSNR, cannot reflect the visual perception to the image effectively. Concerming this issue a content-based image quality assessment metric is proposed in this paper. Based on a structural-similarity-based metric(SSIM) with some modifications, our approach partitions an image into three parts: edges, textures and flat regions according the content of the image and then we apply the SSIMs to fuse each part using Sugeno fuzzy integral. The new metric combines the position and quantity information with the similarity of the image structural information and gives comprehensive evaluation to the quality of the specified image. The experiment results illustrate that the proposed metric has good correlation to the subjective perception, and can reflect the image quality effectively.