Work

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

Year: 2007

Type: article

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.

Source: Journal of the Optical Society of America A

DOI: 10.1364/josaa.24.003418

Authors: Christophe Charrier, Laurence T. Maloney, Hocine Cherifi, Kenneth Knoblauch

Institutions: Laboratoire Universitaire des Sciences Appliquées de Cherbourg, Université de Caen Normandie, New York University, Université de Bourgogne, Inserm

Language: English

Topic: Image and Video Quality Assessment

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Institutes of Health, National Eye Institute

Awards: G4623100990, Dynamics of Multisensory Cue Integration