Back to articles
article
Volume: 54 | Article ID: art00002
Image
Image-Individualized Gamut Mapping Algorithms
  DOI :  10.2352/J.ImagingSci.Technol.2010.54.3.030201  Published OnlineMay 2010
Abstract

In this article the authors show that image quality measures can be successfully used to develop image-individualized gamut mapping algorithms. First the authors compare different image quality measures for the gamut mapping problem and then validate them using psychovisual data from four recent gamut mapping studies. The scoring function used to validate the quality measures is the hit rate, i.e., the percentage of correct choice predictions on data from psychovisual tests. Some of the image quality measures predict the observer's preferences as good as scaling methods such as Thurstones method, which is used to evaluate the psychovisual tests. This is remarkable because the scaling methods are based on the experimental data, whereas the quality measures are independent of these data. The best performing image quality measure is used to automatically select the optimal gamut mapping algorithm for an individual image.

Subject Areas :
Views 26
Downloads 1
 articleview.views 26
 articleview.downloads 1
  Cite this article 

Zofia Barań,czuk, Peter Zolliker, Joachim Giesen, "Image-Individualized Gamut Mapping Algorithmsin Journal of Imaging Science and Technology,  2010,  pp 30201-1 - 30201-7,  https://doi.org/10.2352/J.ImagingSci.Technol.2010.54.3.030201

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2010
  Login or subscribe to view the content