Image Quality Assessment Based on Measuring the Degradation in Geometrical Structural Information

机译：基于测量几何结构信息退化的图像质量评估

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A new image quality metric based on measuring the loss of the structural information inherent in digital images is presented in this paper. The structural information is defined statistically and geometrically in a block basis. Statistical structure information includes luminance means and contrast. Geometrical structure information is extracted from the binary quantization that preserves the first two moments of the image block. To verify the validity of the proposed metric is evaluated against a large amount of test images in LIVE database and compared with that of the famous MSSIM. The cross-distortion test results show that the proposed metric outperforms MSSIM in judging the distorted images corrupted by JPEG2000, Gaussian blurring and fast fading and has the performance close to MSSIM in judging the distorted images corrupted by JPEG and white noises.

机译：本文提出了一种基于测量数字图像固有的结构信息损失的新图像质量度量。结构信息是在块的基础上进行统计和几何定义的。统计结构信息包括亮度平均值和对比度。从保留图像块的前两个时刻的二进制量化中提取几何结构信息。为了验证所提出度量的有效性，对LIVE数据库中的大量测试图像进行了评估，并与著名的MSSIM进行了比较。交叉失真测试结果表明，所提出的度量标准在判断JPEG2000损坏的失真图像，高斯模糊和快速褪色方面优于MSSIM，并且在判断JPEG损坏的失真图像和白噪声方面具有接近MSSIM的性能。

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《Asia-Pacific Signal and Information Processing Association Annual Summit and Conference》|2011年|1-4|共4页
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Chun-Hsien Chou; Yun-Hsiang Hsu;
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中图分类计算机的应用;信号处理;
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4. Image Quality Assessment Based on Measuring the Degradation in Geometrical Structural Information [C] . Chun-Hsien Chou, Yun-Hsiang Hsu Asia-Pacific Signal and Information Processing Association Annual Summit and Conference . 2011

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Image Quality Assessment Based on Measuring the Degradation in Geometrical Structural Information

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