Comparison of image quality assessment algorithms on compressed images

Christophe Charrier; Kenneth Knoblauch; Anush K. Moorthy; Alan C. Bovik; Laurence T. Maloney

doi:10.1117/12.840221

18 January 2010 Comparison of image quality assessment algorithms on compressed images

Christophe Charrier, Kenneth Knoblauch, Anush K. Moorthy, Alan C. Bovik, Laurence T. Maloney

Proceedings Volume 7529, Image Quality and System Performance VII; 75290B (2010) https://doi.org/10.1117/12.840221
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States

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.

Citation Download Citation

Christophe Charrier, Kenneth Knoblauch, Anush K. Moorthy, Alan C. Bovik, and Laurence T. Maloney "Comparison of image quality assessment algorithms on compressed images", Proc. SPIE 7529, Image Quality and System Performance VII, 75290B (18 January 2010); https://doi.org/10.1117/12.840221

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