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Image Quality Assessment Method Based on Contourlet Transform and Generalized Gamma Distribution

机译:基于Contourlet变换和广义伽马分布的图像质量评估方法

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摘要

This paper proposes a new image quality assessment approach based on Contourlet transform and generalized gamma distribution (GGD). The image is processed by Contourlet transform at first and the Contouelet coefficients are modeled by GGD. The parameter of GGD is estimated and the feature vector is formed by combining the parameter of GGD. The feature vector is fed to the support vector machine for training and testing. Experimental results on LIVE database show that our approach has good correlation with the subjective character of human vision.
机译:本文提出了一种基于Contourlet变换和广义伽马分布(GGD)的新的图像质量评估方法。第一图像通过Contourlet变换首先由Contourlet变换处理,并且Contouelet系数由GGD建模。估计GGD的参数,并且通过组合GGD的参数来形成特征向量。特征向量被馈送到支持向量机以进行培训和测试。实时数据库的实验结果表明,我们的方法与人类视力的主观特征有良好的相关性。

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