期刊文献+

基于空间依存的无参考图像质量评价 被引量:2

No-reference image quality assessment based on spatial dependency
下载PDF
导出
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。 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 TID2013,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.
出处 《光学精密工程》 EI CAS CSCD 北大核心 2015年第11期3211-3218,共8页 Optics and Precision Engineering
基金 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)
关键词 二元空间依存 无参考图像质量评价 小波分解 广义高斯分布 binary spatial dependency no-reference image quality assessment wavelet decomposition generalized Gaussian distribution
  • 相关文献

参考文献30

  • 1WANG Z, SIMONCELLI E P, BOVIK A C. Multi-scale Structural Similarity for Image Quality Assessment (Invited Paper) [C]. Proceedings of 37th IEEE Asilomar Conference on Signals, Sys- tems and Computers, Pacific Grove, CA, 2003: 1398-1402.
  • 2WANG Z, BOVIK A C, SHEIKH H R, et al.. Image quality assessment: from error visibility to structural similarity [J]. IEEE Transactions on Image Processing, 2004, 13(4): 600-612.
  • 3CHEN M J, BOVIK A C. Fast structural similarity index algorithm [J]. Journal of Real-Time Image Processing, 2011, 6(4): 281-287.
  • 4SAMPAT M P, WANG Z, GUPTA S, et al.. Complex wavelet structural similarity: a new image similarity index [J]. IEEE Transactions on Image Processing, 2009, 18(11) 2385-2401.
  • 5SHEIKH H R, BOVIK A C, CORMACK L K. Blind quality assessment of JPEG2000 compressed images using natural scene statistics (Invited Pa- per) [C]. Proceedings of 37th IEEE Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, 2003.. 1403-1407.
  • 6SAAD M A, BOVIK A C. Blind image quality as- sessment: A natural scene statistics approach in the DCT domain [J]. IEEE Transactions on linage Processing, 2012, 21(8).. 3339-3352.
  • 7ZHANG M, MURAMATSU C, ZHOU X R. Blind image quality assessment using the joint statistics of generalized local binary pattern [J]. IEEE Signal Processing Letters, 2015, 22(2) :207-210.
  • 8ZHANG Y, MOORTHY A K, CHANDLER D M. C-DIIVINE.. No-reference image quality assessment based on local magnitude and phase statistics of nat- ural scenes [J]. Signal Processing Image Commu- nication, 2014, 29.. 725-747.
  • 9陈勇,李愿,吕霞付,谢正祥,冯鹏.视觉感知的彩色图像质量积极评价[J].光学精密工程,2013,21(3):742-750. 被引量:24
  • 10袁飞,黄联芬,姚彦.基于视觉掩盖效应和奇异值分解的图像质量评测方法[J].光学精密工程,2008,16(4):706-713. 被引量:19

二级参考文献50

共引文献41

同被引文献6

引证文献2

二级引证文献22

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部