• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2016, Vol. 38 ›› Issue (04): 726-732.

• 论文 • 上一篇    下一篇

基于变差函数全局纹理增强的结构相似度图像质量评价

王威1,刘婧1,李骥1,刘洋1,潘伟2   

  1. (1.长沙理工大学计算机与通信工程学院,湖南 长沙 410114;2.中国移动湖南益阳分公司,湖南 益阳 413000)
  • 收稿日期:2015-06-10 修回日期:2015-07-17 出版日期:2016-04-25 发布日期:2016-04-25
  • 基金资助:

    国家安全重大基础研究项目(973)(613XXX0301);博士后科学基金(2013M542467)

Image quality assessment based on structure similarity
with variation function global texture enhancement  

WANG Wei1,LIU Jing1,LI Ji1,LIU Yang1,PAN Wei2   

  1. (1.School of Computer and Communication Engineering,Changsha University of Science & Technology,Changsha 410114;
    2.China Mobile’s Hunan Yiyang Branch,Yiyang 413000,China)
  • Received:2015-06-10 Revised:2015-07-17 Online:2016-04-25 Published:2016-04-25

摘要:

为解决结构相似度算法的图像质量评价缺陷,提出了一种基于变差函数全局纹理增强的结构相似度图像质量评价。该方法首先利用改进的对数变差函数模型提取原图像和失真图像在水平0°、垂直90°和对角45°、135°四个方向的纹理信息特征,然后分别求出对应的纹理增强图像,最后改进SSIM中的结构信息来确定纹理区域的明显失真,计算得到整幅图像的VSSIM值。目前大多数的全参考评价方法不能对数据库中的所有失真类型进行评价,只能对某一类固定的失真类型来评价。本方法对LIVE数据库中的五种失真类型都适用,仿真实验表明,该算法对五种不同失真类型的评价结果具有一定的合理性,并且与主观评价数据库较为一致,其性能也优于其他质量评价模型。

关键词: 结构相似度算法, 对数变差函数, 图像质量评价, 纹理信息

Abstract:

To solve the defects of image quality assessment by structure similarity algorithms, we propose an image quality assessment method based on structure similarity with variation function texture enhancement. Firstly the improved logarithmic variation function model is utilized to extract the texture information characteristics of the original image and  the distorted images in the four directions of horizontal 0°, vertical 90°, diagonal 45° and diagonal 135°, and the corresponding texture enhancement images are calculated respectively. Then the structure information of the improved SSIM is used  to determine the obvious distorted texture region, and the VSSIM value of the whole image is calculated. At present most of the existing evaluation methods are mainly used for a particular type of distortion , while the proposed  method  can be applied to all the five types of distortion in LIVE  database. Experimental results show that  the distortion evaluation results are stable, reasonable and relatively consistent with subjective evaluation database, and its performance is superior to other quality evaluation models.

Key words: structure similarity algorithm;logarithmic variation function;image quality assessment;texture information