第23卷第11期 2015年11月
文章编号
1004-924X(2015)11-3211-08
光学精密工程
Optics and Precision Engineering
基于空间依存的无参考图像质量评价
张闯，王亚明，陈苏婷
Vol.23No.11
Nov.2015
（南京信息工程大学江苏省气象探测与信息处理重点实验室，江苏南京210044）
摘要：为了实时监测图像质量，建立了像素小波系数的二元空间依存关系模型，并利用该模型实现了图像质量的无参考评价。首先，将RGB图像映射到HSV空间；对图像进行小波分解，并建立小波系数的二元空间依存关系模型，即以广义高斯分布来拟合小波系数的二元联合分布。然后，分析二元空间依存关系与图像质量的相关性，建立了无参考图像质量评价指标。最后，对图像质量评价指标进行了测试及对比研究。基于TID2013、LIVE及CSIQ数据库完成了测试，结果表明：基于空间依存的无参考图像质量评价指标可以对图像的失真程度进行准确分级，分级准确率达到96%以上；采用
基于空间依存的无参考图像质量评价方法可以实现对图像质量失真度的准确分级。关键调：二元空间依存；无参考图像质量评价；小波分解；广叉高斯分布
中图分类号：TP391.4
文献标识码：A
doi;10.3788/OPE.20152311.3211
No-reference image qualityassessment based on spatialdependency
ZHANG Chuang',WANG Ya-ming, CHEN Su-ting
(JiangsuKeyLaboratoryof Meteorological ObseruationandInformationProcessing NanjingUniversityofInformationScienceandTechnology,Nanjing210044,China)
Correspondingauthor,E-mail:zhch_76@163.com
Abstract: To monitor the image quality in real-time, a binary spatial dependence model of pixel wavelet coefficients was established, and the model was used to realize the image quality assessment by the no-reference image method. Firstly, the RGB image was mapped into a HSV(Hue,Saturation, Value) space and was processed by wavelet decomposition. A binary space dependent relationship model of wavelet coefficients was established, in which the generalized Gaussian distribution was used to fit the binary joint distribution of wavelet coefficients. Then, the correlation between the binary spatial interdependence relationship and the image quality was analyzed, and the no-reference image quality assesment index was obtained. Finally, the proposed image quality assessment indexes were studied and tested comparatively based on the TID2o13, LIVE and CSIQ databases. The results show that the image quality assesment index based on the spatial dependency can be used to classify the image distortion degree accurately, and the classification accuracy rate reaches above 96%. It concludes that proposed no-reference image method based on the spatial dependency achieves accurate image quality classification
Key words: binary spatial dependency; no-reference image quality assessment; wavelet decomposition;
generalized Gaussian distribution
收稿日期：2015-06-26；修订日期：2015-09-19，
基金项目：中国博士后科学基金资助项目（No.2015M571781)；国家自然科学基金资助项目（No,61271412）