根据小波系数分布参数进行图像质量无参考评价

No-reference Image Quality Assessment Based on Parameters of Wavelet Coefficients Distribution

针对无参考评价算法的普遍适用性问题,提出了一种适用于各种失真类型图像的无参考评价方法.利用自然场景的统计信息进行图像评价,用广义高斯分布拟合小波系数分布,结合拟合参数来度量失真程度,获得对失真图像的客观评价.实验结果表明,该算法广泛适用于各类失真图像,质量评价结果与主观评价有较好的一致性.

We propose a no-reference method for image quality assessment to be used to various types of image distortions. We assess the image using statistic information of natural scenes, and use the generalized Gaussian density model to fit the marginal distribution of wavelet coefficients. Degree of image distortion is measured with the parameter values in the generalized Gaussian density model. Objective assessment of the image quality is obtained by quantifying the difference between the values of scale and shape parameters. Experimental results are consistent with subjective assessments, showing that the proposed method can be applied to most common types of image distortion to give good prediction.