电子学报 ›› 2014, Vol. 42 ›› Issue (7): 1273-1276.DOI: 10.3969/j.issn.0372-2112.2014.07.005

• 学术论文 • 上一篇    下一篇

小波域中CSF频率与方向加权的图像质量评价方法

米曾真   

  1. 重庆理工大学电子信息与自动化学院, 重庆 400054
  • 收稿日期:2013-07-15 修回日期:2013-11-22 出版日期:2014-07-25
    • 作者简介:
    • 米曾真 男,1984年出生,湖南怀化人,于2012年在重庆大学获工学博士学位.现为重庆理工大学电子信息与自动化学院教师.主要从事图像处理、图像质量评价等方面的研究工作.E-mail:lomoer@cqut.edu.cn
    • 基金资助:
    • 国家自然科学基金 (No.51105392); 重庆理工大学科研启动金项目资助

Image Quality Evaluation Method Based on Frequency and Direction Weighted to CSF in Wavelet Domain

MI Zeng-zhen   

  1. College of Electronic Information and Automation, Chongqing University of Technology, Chongqing 400054, China
  • Received:2013-07-15 Revised:2013-11-22 Online:2014-07-25 Published:2014-07-25
    • Supported by:
    • National Natural Science Foundation of China (No.51105392); Research Fund of Chongqing University of Technology

摘要:

为解决结构相似度算法的图像质量评价缺陷,提出一种在小波域中,根据CSF的频率与方向加权的图像质量评价方法.该方法将图像的小波域多分辨率特性与CSF的带通特性有机的相结合,得到一种基于结构相似度的评价新方法.算法首先将频率归一化的CSF曲线按照1倍频程分解成5份,然后进行5级CDF 9/7双正交小波分解与重构,得到一个低频子带LL和多个中高频子带HHiHLiLHi,根据不同的频率,不同的方向分配不同的权重,分别与相应的子频带SSIM值相乘,然后累加运算,得到小波域的加权图像结构相似度WWSSIM.实验表明,WWSSIM方法的单调性、一致性、准确性评价指标较高,更接近人类主观视觉感受.

关键词: 图像质量评价, 结构相似度, 对比度敏感函数, 小波分解与重构

Abstract:

In order to solve the defects of SSIM algorithm for image quality evaluation,frequency and direction weighed to CSF in Wavelet domain was proposed.This method organic combination the multi-resolution characteristics of wavelet with bandpass characteristic of CSF curve,and get a new algorithm based on SSIM.Firstly,the frequency normalized CSF curves according to 1 octave level into five parts,and then 5 levels CDF 9/7 pairs of orthogonal wavelet decomposition and reconstruction,to get a low-frequency sub-band LL and a plurality of medium or high frequency sub-band HHi,HLi and LHi,then assign different weights according to different frequencies,different directions,which were multiplied with the corresponding sub-band SSIM values,and then do accumulate operations to obtain the weighted structural similarity in wavelet domain named WWSSIM.Experiments show that WWSSIM algorithm has high monotonicity,consistency,accuracy,and closer to human subjective visual experience.

Key words: image quality assessment, structural similarity index measurement(SSIM), contrast sensitivity function (CSF), wavelet decomposition and reconstruction

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