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Maximum likelihood difference scaling of image quality in compression-degraded images
Christophe Charrier1, Laurence T Maloney, Hocine Cherifi
1Université de Caen Basse Normandie, LUSAC EA 2807, Groupe Vision & Analyse d'Images, 120 rue de l'Exode, 50000 Saint Lô, France.
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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