In this paper we compare different image quality measures for the gamut mapping problem, and validate them using psycho-visual data from four recent gamut mapping studies. The psycho-visual data are choice data of the form: given an original image and two images obtained by applying different gamut mapping algorithms, an observer chooses the one that reproduces the original image better in his/her opinion. The scoring function used to validate the quality measures is the hit rate, i.e., the percentage of correct choice predictions on data from the psycho-visual tests. We also propose a new image quality measure based on the difference in color and local contrast. This measure compares well to the measures from the literature on our psycho-visual data. Some of these measures predict the observer's preferences equally well as scaling methods like Thurstone's method or conjoint analysis that are used to evaluate the psycho-visual tests. This is remarkable in the sense that the scaling methods are based on the experimental data, whereas the quality measures are independent of this data.
Zofia Barańczuk, Peter Zolliker, Joachim Giesen, "Image Quality Measures for Evaluating Gamut Mapping" in Proc. IS&T 17th Color and Imaging Conf., 2009, pp 21 - 26, https://doi.org/10.2352/CIC.2009.17.1.art00005