Upgrading color-difference formulas
JOSA A, Vol. 27, Issue 7, pp. 1620-1629 (2010)
http://dx.doi.org/10.1364/JOSAA.27.001620
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Abstract
We propose a method to improve the prediction performance of existing color-difference formulas with additional visual data. The formula is treated as the mean function of a Gaussian process, which is trained with experimentally determined color-discrimination data. Color-difference predictions are calculated using Gaussian process regression (GPR) considering the uncertainty of the visual data. The prediction accuracy of the CIE94 formula is significantly improved with the GPR approach for the Leeds and the Witt datasets. By upgrading CIE94 with GPR we achieve a significantly lower STRESS value of 26.58 compared with that for CIEDE2000 (27.49) on a combined dataset. The method could serve to improve the prediction performance of existing color-difference equations around particular color centers without changing the equations themselves.
© 2010 Optical Society of America
OCIS Codes
(330.0330) Vision, color, and visual optics : Vision, color, and visual optics
(330.1690) Vision, color, and visual optics : Color
(330.1730) Vision, color, and visual optics : Colorimetry
ToC Category:
Vision, Color, and Visual Optics
History
Original Manuscript: January 26, 2010
Revised Manuscript: April 15, 2010
Manuscript Accepted: April 19, 2010
Published: June 11, 2010
Virtual Issues
Vol. 5, Iss. 11 Virtual Journal for Biomedical Optics
Citation
Ingmar Lissner and Philipp Urban, "Upgrading color-difference formulas," J. Opt. Soc. Am. A 27, 1620-1629 (2010)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=josaa-27-7-1620
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