A Novel Spatial Pooling Strategy for Image Quality Assessment

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• 作者：Qiaohong Li ; Yu-Ming Fang ; Jing-Tao Xu
• 关键词：image quality assessment ; spatial pooling ; statistical pooling ; support vector regression ; structural similarity
• 刊名：Journal of Computer Science and Technology
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：31
• 期：2
• 页码：225-234
• 全文大小：1,176 KB
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• 作者单位：Qiaohong Li (1)
  Yu-Ming Fang (2)
  Jing-Tao Xu (3)
  
  1. School of Computer Engineering, Nanyang Technological University, Singapore, 639798, Singapore
  2. School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, 330013, China
  3. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, 100086, China
  
• 刊物类别：Computer Science
• 刊物主题：Computer Science, general
  Software Engineering
  Theory of Computation
  Data Structures, Cryptology and Information Theory
  Artificial Intelligence and Robotics
  Information Systems Applications and The Internet
  Chinese Library of Science
  
• 出版者：Springer Boston
• ISSN：1860-4749

文摘

A variety of existing image quality assessment (IQA) metrics share a similar two-stage framework: at the first stage, a quality map is constructed by comparison between local regions of reference and distorted images; at the second stage, the spatial pooling is adopted to obtain overall quality score. In this work, we propose a novel spatial pooling strategy for image quality assessment through statistical analysis of the quality map. Our in-depth analysis indicates that the overall image quality is sensitive to the quality distribution. Based on the analysis, the quality histogram and statistical descriptors extracted from the quality map are used as input to the support vector regression to obtain the final objective quality score. Experimental results on three large public IQA databases have demonstrated that the proposed spatial pooling strategy can greatly improve the quality prediction performance of the original IQA metrics in terms of correlation with human subjective ratings.