Maximum likelihood difference scaling of image quality in compression-degraded images.

Abstract : Lossy image compression techniques allow arbitrarily high compression rates but at the price of poor image quality. We applied maximum likelihood difference scaling to evaluate image quality of nine images, each compressed via vector quantization to ten different levels, within two different color spaces, RGB and CIE 1976 L(*)a(*)b(*). In L(*)a(*)b(*) space, images could be compressed on average by 32% more than in RGB space, with little additional loss in quality. Further compression led to marked perceptual changes. Our approach permits a rapid, direct measurement of the consequences of image compression for human observers.
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Contributor : Kenneth Knoblauch <>
Submitted on : Monday, October 1, 2007 - 10:21:06 AM
Last modification on : Wednesday, August 14, 2019 - 10:46:02 AM
Long-term archiving on : Friday, April 9, 2010 - 4:49:50 PM

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  • HAL Id : inserm-00175755, version 1
  • PUBMED : 17975567

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Christophe Charrier, Laurence Maloney, Hocine Cherifi, Kenneth Knoblauch. Maximum likelihood difference scaling of image quality in compression-degraded images.. Journal of the Optical Society of America. A Optics, Image Science, and Vision, Optical Society of America, 2007, 24 (11), pp.3418-3426. ⟨inserm-00175755⟩

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