articleIEEE Transactions on Image ProcessingAug 17, 2012Closed access

No-Reference Image Quality Assessment in the Spatial Domain

The University of Texas at Austin

PubMed
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Abstract

We propose a natural scene statistic-based distortion-generic blind/no-reference (NR) image quality assessment (IQA) model that operates in the spatial domain. The new model, dubbed blind/referenceless image spatial quality evaluator (BRISQUE) does not compute distortion-specific features, such as ringing, blur, or blocking, but instead uses scene statistics of locally normalized luminance coefficients to quantify possible losses of "naturalness" in the image due to the presence of distortions, thereby leading to a holistic measure of quality. The underlying features used derive from the empirical distribution of locally normalized luminances and products of locally normalized luminances under a spatial…

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Authors

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Topics & keywords

Keywords
  • Distortion (music)
  • Artificial intelligence
  • Image quality
  • Ringing artifacts
  • Computer science
  • Computer vision
  • Image restoration
  • Pattern recognition (psychology)
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