PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Perceptual Analysis of Distance Measures for Color Constancy Algorithms
Arjan Gijsenij, Theo Gevers and Marcel Lucassen
Journal of the Optical Society of America A Volume 26, Number 10, pp. 2243-2256, 2009.

Abstract

Color constancy algorithms are often evaluated by using a distance measure that is based on mathematical principles, such as the angular error. However, it is unknown whether these distance measures correlate to human vision. Therefore, the main goal of our paper is to analyze the correlation between several performance measures and the quality, obtained by using psychophysical experiments, of the output images generated by various color constancy algorithms. Subsequent issues that are addressed are the distribution of performance measures, suggesting additional and alternative information that can be provided to summarize the performance over a large set of images, and the perceptual significance of obtained improvements, i.e., the improvement that should be obtained before the difference becomes noticeable to a human observer.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:6159
Deposited By:Christof Monz
Deposited On:08 March 2010