• 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 • Previous Articles     Next Articles

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

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