结合结构信息和亮度统计的无参考图像质量评价

摘要

基于非下采样Contourlet变换（Nonsubsampled Contourlet Transform，NSCT）子带系数间的结构相关性，本文提出了一种通用的无参考图像质量评价方法。首先，利用互信息分析NSCT子带系数间的相关性，确定出相关性比较强的子带系数；其次，分别计算这些子带系数间的结构信息比较算子，以此作为描述图像结构相关性的统计特征；进而，结合空间域亮度均值减损对比归一化（Mean Subtracted Contrast Normalized，MSCN）系数及其邻域系数的统计特征，分别构造相应的无参考图像质量评价模型和图像失真类型识别模型；最后，在LIVE等图像质量评价数据库上进行了大量的实验仿真。仿真结果表明，评价模型的评价结果与人类主观评价具有非常高的相关性，与当今主流评价算法相比非常具有竞争性。%Based on the correlation between subband coefficients of nonsubsampled contourlet transform(NSCT),a general-purpose no-reference image quality assessment(NR-IQA)method is proposed.Firstly,the correlation between NSCT subband coefficients was analyzed using mutual information and the subband coefficients with strong correlation were deter-mined.Secondly,the structure comparison operator of those subband coefficients were calculated respectively and used to de-scribe the statistics characteristic of image structure information.Moreover,a no-reference image quality assessment model and an image distortion type recognition model were constructed by combining the statistical features of the mean subtracted contrast normalized(MSCN)coefficients and the structural similarity of NSCT coefficients.Finally,a large number of simu-lation experiments were carried out in the LIVE image quality evaluation database.The simulation results show that this method is suitable for many common image distortion types and correlates well with the human judgments of image quality, and the assessment model is competitive with the nowadays’mainstream evaluation method.