基于Gaussian-Hermite矩和HVS的图像质量评价

doi:10.7523/j.issn.2095-6134.2017.03.013

中国科学院大学学报 ›› 2017, Vol. 34 ›› Issue (3): 389-394.DOI: 10.7523/j.issn.2095-6134.2017.03.013

基于Gaussian-Hermite矩和HVS的图像质量评价

李国庆^1,2, 朱百明¹, 齐洪钢³, 黄鑫¹, 尹洪胜¹

1. 江苏联合职业技术学院, 江苏徐州;
2. 中国矿业大学信息与控制工程学院, 江苏徐州 221116;
3. 中国科学院大学, 北京 100049

收稿日期:2016-11-20 修回日期:2017-02-20 发布日期:2017-05-15
通讯作者: 齐洪钢,E-mail:hgqi@ucas.ac.cn
基金资助:
国家自然科学基金（61379100，61472388）资助

Image quality assessment based on Gaussian-Hermite moments and HVS

LI Guoqing^1,2, ZHU Baiming¹, QI Honggang³, HUANG Xin¹, YIN Hongsheng¹

1. Jiangsu Union Technical Institute, Xuzhou;
2. School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China;
3. University of Chinese Academy of Sciences, Beijing 100049, China

Received:2016-11-20 Revised:2017-02-20 Published:2017-05-15

摘要/Abstract

摘要： 提出一种基于Gaussian-Hermite矩和人类视觉系统（HVS）特性融合的图像全参考质量评价方法。正交矩在图像处理和模式识别方面有很重要的作用。图像的低阶矩能很好地表征图像的特征，可用于图像质量的准确评价。该方法首先通过计算两幅图像间连续正交矩能量差异获得低阶矩特征；然后，结合HVS的掩盖效应对图像的不同区域分配不同权重；最后，对图像所有分区的连续正交矩能量差进行加权平均得到图像质量分数。在国际通用的图像质量评价数据集中，对所提出的方法进行测试。实验结果对比表明，该方法具有很好的效果。

关键词: Gaussian-Hermite矩, 图像质量评价, 正交矩能量差异, 人类视觉系统, 掩盖效应

Abstract: We present a new full-reference image quality metric using Gaussian-Hermite moments and human visual system (HVS). Orthogonal moments are powerful tools in pattern recognition and image processing applications. Low-order moments well characterize features of an image and can be used to assess the image quality accurately. Firstly the proposed method obtains the feature of low-order moments through computing the continuous orthogonal moment energy differences between two images. Then, by combining the masking effect of human visual system (HVS), the different weighting factors are assigned to different areas in an image. Finally, image quality scores are derived by the weighted average of the continuous orthogonal moment energy differences in all the areas of the image. The performance of the proposed method is evaluated on several public databases. Experimental results and comparisons demonstrate the efficiency of the method.

Key words: Gaussian-Hermite moments, image quality assessment, the orthogonal moment energy differences, human visual system, masking effect

中图分类号:

TP391.41

李国庆, 朱百明, 齐洪钢, 黄鑫, 尹洪胜. 基于Gaussian-Hermite矩和HVS的图像质量评价[J]. 中国科学院大学学报, 2017, 34(3): 389-394.

LI Guoqing, ZHU Baiming, QI Honggang, HUANG Xin, YIN Hongsheng. Image quality assessment based on Gaussian-Hermite moments and HVS[J]. , 2017, 34(3): 389-394.

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基于Gaussian-Hermite矩和HVS的图像质量评价

Image quality assessment based on Gaussian-Hermite moments and HVS

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