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Natural scene statistics based blind image quality assessment in spatial domain

We propose a natural scene statistic based quality assessment model Refer- enceless Image Spatial QUality Evaluator (RISQUE) which extracts marginal statistics of local normalized luminance signals and measures 'un-naturalness' of the distorted image based on measured deviation of them. We also model distribution of pairwise products of adjacent normalized luminance signals providing us with orientation distortion information. Although multi-scale, the model is defined in the space domain avoiding costly frequency or wavelet transforms. The frame work is simple, fast, human perception based and shown to perform statistically better than other proposed no reference algorithms and full reference structural similarity index(SSIM). / text

Identiferoai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2011-05-3220
Date05 August 2011
CreatorsMittal, Anish
Source SetsUniversity of Texas
LanguageEnglish
Detected LanguageEnglish
Typethesis
Formatapplication/pdf

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