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Proceedings Paper

Comparison of image quality assessment algorithms on compressed images
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Paper Abstract

A crucial step in image compression is the evaluation of its performance, and more precisely the available way to measure the final quality of the compressed image. Usually, to measure performance, some measure of the covariation between the subjective ratings and the degree of compression is performed between rated image quality and algorithm. Nevertheless, local variations are not well taken into account. We use the recently introduced Maximum Likelihood Difference Scaling (MLDS) method to quantify suprathreshold perceptual differences between pairs of images and examine how perceived image quality estimated through MLDS changes the compression rate is increased. This approach circumvents the limitations inherent to subjective rating methods.

Paper Details

Date Published: 18 January 2010
PDF: 11 pages
Proc. SPIE 7529, Image Quality and System Performance VII, 75290B (18 January 2010); doi: 10.1117/12.840221
Show Author Affiliations
Christophe Charrier, GREYC UMR 6072, CNRS, Univ. de Caen Basse-Nomandie (France)
Kenneth Knoblauch, INSERM (France)
Anush K. Moorthy, The Univ. of Texas at Austin (United States)
Alan C. Bovik, The Univ. of Texas at Austin (United States)
Laurence T. Maloney, New York Univ. (United States)

Published in SPIE Proceedings Vol. 7529:
Image Quality and System Performance VII
Susan P. Farnand; Frans Gaykema, Editor(s)

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