一个图像质量盲评估的统计测度

doi:10.3969/j.issn.0372-2112.2014.07.027

电子学报 ›› 2014, Vol. 42 ›› Issue (7): 1419-1423.DOI: 10.3969/j.issn.0372-2112.2014.07.027

一个图像质量盲评估的统计测度

黄虹, 张建秋

复旦大学电子工程系, 上海 200433

收稿日期:2013-03-22 修回日期:2013-12-08 出版日期:2014-07-25
- 作者简介:
- 黄虹女.1988年8月出生，福建宁德人.2010年本科、2013年硕士毕业于复旦大学电子工程系，在校期间从事数字信号处理方面的有关研究.E-mail：10210720031@fudan.edu.cn；张建秋 男.1962年生于湖南省隆回县.现任复旦大学电子工程系教授、博士生导师，IEEE高级会员，主要研究领域有信息处理理论及其在测量和仪器、新型传感器、控制和通信中的应用.E-mail：jqzhang01@fudan.edu.cn
- 基金资助:
- 国家自然科学基金 (No.61171127）

A Statistical Measure for Blind Image Quality Assessment

HUANG Hong, ZHANG Jian-qiu

Department of Electronic Engineering, Fudan University, Shanghai 200433, China

Received:2013-03-22 Revised:2013-12-08 Online:2014-07-25 Published:2014-07-25

摘要/Abstract

摘要：

本文提出了一个图像质量盲评估的统计测度.该测度首先根据自然图像的统计性质与失真图像的模型，实现对图像小波系数分布参数的盲估计；再利用估计的分布参数来计算失真图像与参考图像之间的互信息，以量化失真图像对参考图像的保真度，进而实现对图像质量的评估.本文提出的测度避免了对参考图像的依赖，且克服了现有图像质量盲评估对特征选择与提取、机器学习等过程的依赖.LIVE图像质量评估数据库的总体评估结果表明：本文提出的盲评估统计测度对图像质量评估结果与数据库的主观评估结果高度一致，且优于文献中报道的盲评估测度.

关键词: 图像质量盲评估, 保真度, 互信息, 自然场景统计模型, 高斯尺度混合模型

Abstract:

A statistical measure for blind image quality assessment (IQA) is proposed.The wavelet coefficients' distribution parameters of the distorted images are blind estimated based on the natural scene statistics and the image distortion model;the mutual information between the distorted and the corresponding reference images is further calculated from the estimated distribution parameters.The quantified information fidelity is regarded as an efficient image quality assessment criterion.The proposed statistical measure in this paper does not require any prior information of the reference image and avoids the feature selection,feature extraction and machine learning processes required by existing blind image quality assessment methods.Evaluated on the LIVE IQA database,it is demonstrated that the proposed statistical measure corresponds well with the subjective human evaluations and outperforms the state-of-art blind IQA algorithms.

Key words: blind image quality assessment, mutual information, information fidelity, natural scene statistics (NSS) model, Gaussian scale mixture (GSM) model

中图分类号:

TP391

黄虹, 张建秋. 一个图像质量盲评估的统计测度[J]. 电子学报, 2014, 42(7): 1419-1423.

HUANG Hong, ZHANG Jian-qiu. A Statistical Measure for Blind Image Quality Assessment[J]. Acta Electronica Sinica, 2014, 42(7): 1419-1423.

参考文献

[1] Sheikh H R,Sabir M F,Bovik A C.A statistical evaluation of recent full reference image quality assessment algorithms[J].IEEE Transactions on Image Processing,2006,15(11):3440-3451.
[2] Wang Z.Applications of objective image quality assessment methods[J].IEEE Signal Processing Magazine,2011,28(6):137-142.
[3] Sheikh H R,Bovik A C.Image information and visual quality[J].IEEE Transactions on Image Processing,2006,15(2):430-444.
[4] Wang Z,Bovik A C,Sheikh H R,Simoncelli E P.Image quality assessment:from error measurement to structural similarity[J].IEEE Transactions on Image Processing,2006,13(4):600-612.
[5] Saad M A,Bovik A C,Charrier C.DCT statistics model-based blind image quality assessment[A].18th International Conference on Image Processing[C].USA:IEEE,2011.3093-3096.
[6] Moorthy A K,Bovik A C.Blind image quality assessment:from natural scene statistics to perceptual quality[J].IEEE Transactions on Image Processing,2011,20(12):3350-3363.
[7] Mittal A,Muralidhar G S,Ghosh J,et al.Blind image quality assessment without human training using latent quality factors[J].IEEE Signal Processing Letters,2012,19(2):75-78.
[8] Gabarda S,Cristobal G.Blind image quality assessment through anisotropy[J].Journal of the Optical Society of America A,2007,24(12):B42-B51.
[9] Wainwright M J,Simoncelli E P.Scale mixtures of Gaussians and the statistics of natural images[A].Neural Information Processing Systems Foundation (NIPS)[C].Denver:MIT Press,1999.855-861.
[10] Portilla J,Strela V,Wainwright M J,Simoncelli E P.Image denoising using scale mixture of Gaussians in the wavelet domain[J].IEEE Transactions on Image Processing,2003,12(11):1338-1351.
[11] Sheikh H R,Bovik A C,De Veciana G.An information fildelity criterion for image quality assessment using natural scene statistics[J].IEEE Transactions on Image Processing,2005,14(12):2117-2128.
[12] Li Q,Wang Z.Reduced-reference image quality assessment using divisive normalization-based image representation[J].IEEE Journal of Selected Topics in Signal Processing,2009,3(2):202-211.
[13] Moorthy A K,Bovik A C.Statistics of natural image distortions[A].IEEE International Conference on Acoustics Speech and Signal Processing[C].USA:IEEE,2010.962-965.
[14] Sheikh H R,Wang Z,Bovik A C,Cormack L K.LIVE Image Quality Assessment Database Release 2[OL].http://live.ece.utexas.edu/research/quality,2011-12-20.
[15] Moorthy A K,Bovik A C.Distortion Identification-based image Verity and Integrity Evaluation (DIIVINE) Index[OL].http://live.ece.utexas.edu/research/quality/index.htm,2012-02-16.

一个图像质量盲评估的统计测度

A Statistical Measure for Blind Image Quality Assessment

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	尤殿龙, 郭松, 赵春慧, 原福永, 申利民, 陈真. 面向分类的流特征在线特征选择算法[J]. 电子学报, 2020, 48(2): 321-332.
[2]	彭丝雨, 周到, 张家琦, 王宇, 高军峰. 基于互信息的脑网络及测谎研究[J]. 电子学报, 2019, 47(7): 1551-1556.
[3]	李庆武, 马云鹏, 周亚琴, 邢俊. 基于无监督栈式降噪自编码网络的显著性检测算法[J]. 电子学报, 2019, 47(4): 871-879.
[4]	雷维嘉, 宋海娜, 陈胜男, 谢显中. 基于无率纠错码和高阶QAM调制的收端速率自适应方案[J]. 电子学报, 2017, 45(8): 2001-2007.
[5]	马润年, 王班, 王刚, 郭晓成, 刘文斌. 基于互信息的通信网络节点重要性度量方法[J]. 电子学报, 2017, 45(3): 747-752.
[6]	张晴晖, 张榆锋, 林文晶, 周屹, 章克信, 高莲. 颈动脉B超估计血管壁搏动位移的干扰抑制[J]. 电子学报, 2017, 45(12): 2903-2908.
[7]	续欣莹, 张扩, 谢珺, 谢刚. 基于互信息下粒子群优化的属性约简算法[J]. 电子学报, 2017, 45(11): 2695-2704.
[8]	宋岚, 文堂柳, 黎海生, 王杉. 基于云模型、图论和互信息的遥感影像分割方法[J]. 电子学报, 2015, 43(8): 1518-1525.
[9]	张博;景晓军;孙松林;张少乐. 基于梯度离散度和互信息准则的残缺指纹方向场重建融合算法[J]. 电子学报, 2011, 39(9): 2130-2134.
[10]	马建华;陈武凡;黄静;杨迪;毕一鸣. 基于最大互信息量熵差分割的CT金属伪影消除[J]. 电子学报, 2009, 37(8): 1779-1783.
[11]	袁华强;叶阳东;刘东. 遗传顺序IB算法[J]. 电子学报, 2009, 37(8): 1804-1809.
[12]	周宁宁;赵正旭;秦文虎. 图像的中介滤波算法与图像中介保真度度量[J]. 电子学报, 2008, 36(5): 979-984.
[13]	刘兆广;彭玉华;杨阳. 一种基于类haar小波的MCTF视频编码方案[J]. 电子学报, 2008, 36(2): 386-391.
[14]	杨静;胡顺波;刘常春;杨金宝. 基于简单Schur凹函数的图像配准测度研究[J]. 电子学报, 2008, 36(12): 2328-2332.
[15]	杨健, 王涌天, 唐宋元, 周寿军, 刘越. 基于互信息量和薄板样条的X射线造影图像弹性配准[J]. 电子学报, 2007, 35(1): 127-130.