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Proceedings Article

Blind image quality assessment without training on human opinion scores

[+] Author Affiliations
Anish Mittal, Rajiv Soundararajan, Gautam S. Muralidhar, Alan C. Bovik, Joydeep Ghosh

The Univ. of Texas at Austin (United States)

Proc. SPIE 8651, Human Vision and Electronic Imaging XVIII, 86510T (March 14, 2013); doi:10.1117/12.981761
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From Conference Volume 8651

  • Human Vision and Electronic Imaging XVIII
  • Bernice E. Rogowitz; Thrasyvoulos N. Pappas; Huib de Ridder
  • Burlingame, California, USA | February 03, 2013

abstract

We propose a family of image quality assessment (IQA) models based on natural scene statistics (NSS), that can predict the subjective quality of a distorted image without reference to a corresponding distortionless image, and without any training results on human opinion scores of distorted images. These `completely blind' models compete well with standard non-blind image quality indices in terms of subjective predictive performance when tested on the large publicly available `LIVE' Image Quality database. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Anish Mittal ; Rajiv Soundararajan ; Gautam S. Muralidhar ; Alan C. Bovik and Joydeep Ghosh
" Blind image quality assessment without training on human opinion scores ", Proc. SPIE 8651, Human Vision and Electronic Imaging XVIII, 86510T (March 14, 2013); doi:10.1117/12.981761; http://dx.doi.org/10.1117/12.981761


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