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Proceedings Paper

Predicting the performance of a spatial gamut mapping algorithm
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Paper Abstract

Gamut mapping algorithms are currently being developed to take advantage of the spatial information in an image to improve the utilization of the destination gamut. These algorithms try to preserve the spatial information between neighboring pixels in the image, such as edges and gradients, without sacrificing global contrast. Experiments have shown that such algorithms can result in significantly improved reproduction of some images compared with non-spatial methods. However, due to the spatial processing of images, they introduce unwanted artifacts when used on certain types of images. In this paper we perform basic image analysis to predict whether a spatial algorithm is likely to perform better or worse than a good, non-spatial algorithm. Our approach starts by detecting the relative amount of areas in the image that are made up of uniformly colored pixels, as well as the amount of areas that contain details in out-of-gamut areas. A weighted difference is computed from these numbers, and we show that the result has a high correlation with the observed performance of the spatial algorithm in a previously conducted psychophysical experiment.

Paper Details

Date Published: 19 January 2009
PDF: 9 pages
Proc. SPIE 7241, Color Imaging XIV: Displaying, Processing, Hardcopy, and Applications, 724116 (19 January 2009); doi: 10.1117/12.805852
Show Author Affiliations
Arne M. Bakke, Gjøvik Univ. College (Norway)
Ivar Farup, Gjøvik Univ. College (Norway)
Jon Y. Hardeberg, Gjøvik Univ. College (Norway)


Published in SPIE Proceedings Vol. 7241:
Color Imaging XIV: Displaying, Processing, Hardcopy, and Applications
Reiner Eschbach; Gabriel G. Marcu; Shoji Tominaga; Alessandro Rizzi, Editor(s)

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