吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (2): 639-645.doi: 10.13229/j.cnki.jdxbgxb201602045

• 论文 • 上一篇    下一篇

基于Contourlet统计特性的无参考图像质量评价

焦淑红1, 齐欢1, 林维斯2, 唐琳1, 申维和3   

  1. 1.哈尔滨工程大学 信息与通信工程学院, 哈尔滨 150001;
    2.南洋理工大学 计算机工程学院, 新加坡 639798;
    3.中国运载火箭技术研究院 空间物理重点实验室, 北京100076
  • 收稿日期:2014-08-28 出版日期:2016-02-20 发布日期:2016-02-20
  • 通讯作者: 齐欢(1989-),女,博士研究生.研究方向:图像处理与机器视觉.E-mail:heuqihuan@163.com E-mail:jiaoshuhong@hrbeu.edu.com
  • 作者简介:焦淑红(1966-),女,教授,博士.研究方向:图像处理与机器视觉.E-mail:jiaoshuhong@hrbeu.edu.com
  • 基金资助:
    国家自然科学基金项目(61201238)

No-reference quality assessment based on the statistics in Cntourlet domain

JIAO Shu-hong1, QI Huan1, LIN Wei-si2, TANG Lin1, SHEN Wei-he3   

  1. 1.College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China;
    2.School of Computer Engineering,Nanyang Technological University,Singapore 639798,Singapore;
    3.Science and Technology on Space Physics Laboratory,China Academy of Launch Vehicle Technology,Beijing 100076,China
  • Received:2014-08-28 Online:2016-02-20 Published:2016-02-20

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摘要： 利用Contourlet统计特征建立自然统计模型与待评价图像模型,提出了Contourlet域无参考图像质量评价方法(SCIQA).通过在主观数据库上的实验表明,无论同种干扰类型的图像还是多种干扰图像集合,SCIQA均明显优于经典全参考算法和通用型无参考算法,并且具有较强的通用性.

关键词: 信息处理技术, 图像质量评价, Contourlet统计特征

Abstract: The statistic features in Cntourlet domain are employed to build the natural statistic model and the tested image model first. Then a no-reference assessment algorithm in Contourlet domain (SCIQR) is proposed. Experiment results on subjective databases show that SCIQR outperforms the classical full-reference image quality assessment algorithm and the universal no-reference algorithm no-matter on single distortion type images and on the set of different types of distortion images. This demonstrates that SCIQR has good universality.

Key words: information processing technology, image quality assessment, statistics in Contourlet domain

中图分类号: 

  • TN911
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