作者投稿和查稿 主编审稿 专家审稿 编委审稿 远程编辑

计算机工程 ›› 2011, Vol. 37 ›› Issue (14): 226-227. doi: 10.3969/j.issn.1000-3428.2011.14.076

• 图形图像处理 • 上一篇    下一篇

边缘加权的结构相似性测度

吕 鹏,张建秋   

  1. (复旦大学电子工程系,上海 200433)
  • 收稿日期:2010-12-30 出版日期:2011-07-20 发布日期:2011-07-20
  • 作者简介:吕 鹏(1986-),男,硕士研究生,主研方向:图像处理,质量评估;张建秋,教授、博士生导师、IEEE高级会员
  • 基金资助:

    国家自然科学基金资助项目(60872059)

Edge-weighted Structural Similarity Index

LV Peng, ZHANG Jian-qiu   

  1. (Dept. of Electronic Engineering, Fudan University, Shanghai 200433, China)
  • Received:2010-12-30 Online:2011-07-20 Published:2011-07-20

摘要:

针对结构相似性测度(SSIM)不能较好地客观评价图像模糊与强高斯噪声失真的问题,提出一种边缘加权的结构相似性测度(EWSSIM),以符合人眼视觉系统(HVS)特性。EWSSIM将原始图像和失真图像的整体轮廓信息与局部纹理细节信息加权,更充分地描述图像的结构相似度。通过LIVE图库的仿真结果表明,与SSIME相比,WSSIM能够更好地评价图像模糊与强高斯噪声失真,且在各类失真图像的评价一致性上优于SSIM。

关键词: 图像质量评估, 结构相似性测度, 边缘检测, 边缘加权结构相似性测度

Abstract:

This paper proposes an Edge-weighted Structural Similarity Index(EWSSIM), which can match well with Human Vision System(HVS). Structural Similarity Image quality assessment(SSIM) does not evaluate highly blurred and Gaussian white noise distorted images well. EWSSIM assigns different weights to contour correlation and local texture correlation of the original image and distorted image, which can represent structural similarity better than SSIM. Experimental results of LIVE image database indicate that the proposed index outperforms SSIM in blurred and Gaussian white noise distorted images and also gives a better coherent evaluation for all kinds of distortions in LIVE database.

Key words: image quality assessment, Structural Similarity index(SSIM), edge detection, Edge-weighted Structural Similarity Index(EWSSIM)

中图分类号: