Foveation-based image quality assessment

Wen Jiin Tsai*, Yi Shih Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Since human vision has much greater resolutions at the center of our visual field than elsewhere, different criteria of quality assessment should be applied on the image areas with different visual resolutions. This paper proposed a foveation-based image quality assessment method which adopted different sizes of windows in quality assessment for a single image. Visual salience models which estimate visual attention regions are used to determine the foveation center and foveation resolution models are used to guide the selection of window sizes for the areas over spatial extent of the image. Finally, the quality scores obtained from different window sizes are pooled together to get a single value for the image. The proposed method has been applied to IQA metrics, SSIM, PSNR, and UQI. The result shows that both Spearman and Kendall correlation coefficients can be improved significantly by our foveation-based method.

Original languageEnglish
Title of host publication2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages25-28
Number of pages4
ISBN (Electronic)9781479961399
DOIs
StatePublished - 27 Feb 2015
Event2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014 - Valletta, Malta
Duration: 7 Dec 201410 Dec 2014

Publication series

Name2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014

Conference

Conference2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014
CountryMalta
CityValletta
Period7/12/1410/12/14

Keywords

  • foveation
  • human visual system
  • Image quality assessment
  • visual salience model

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    Tsai, W. J., & Liu, Y. S. (2015). Foveation-based image quality assessment. In 2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014 (pp. 25-28). [7051495] (2014 IEEE Visual Communications and Image Processing Conference, VCIP 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VCIP.2014.7051495