articleIEEE Transactions on Image ProcessingNov 23, 2010Closed access

Information Content Weighting for Perceptual Image Quality Assessment

University of Waterloo

PubMed
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Abstract

Many state-of-the-art perceptual image quality assessment (IQA) algorithms share a common two-stage structure: local quality/distortion measurement followed by pooling. While significant progress has been made in measuring local image quality/distortion, the pooling stage is often done in ad-hoc ways, lacking theoretical principles and reliable computational models. This paper aims to test the hypothesis that when viewing natural images, the optimal perceptual weights for pooling should be proportional to local information content, which can be estimated in units of bit using advanced statistical models of natural images. Our extensive studies based upon six publicly-available subject-rated image databases…

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1,304
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Authors

2

Topics & keywords

Keywords
  • Pooling
  • Weighting
  • Image quality
  • Computer science
  • Distortion (music)
  • Artificial intelligence
  • Pattern recognition (psychology)
  • Data mining
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