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CMC 2000 chromatic adaptation transform: CMCCAT2000

CMC 2000 chromatic adaptation transform: CMCCAT2000 CMCCAT97 is a chromatic adaptation transform included in CIECAM97s, the CIE 1997 colour appearance model, for describing colour appearance under different viewing conditions and is recommended by the Colour Measurement Committee of the Society of Dyers and Colourists for predicting the degree of colour inconstancy of surface colours. Among the many transforms tested, this transform gave the most accurate predictions to a number of experimental data sets. However, the structure of CMCCAT97 is considered complicated and causes problems when applications require the use of its reverse mode. This article describes a simplified version of CMCCAT97— CMCCAT2000—which not only is significantly simpler and eliminates the problems of reversibility, but also gives a more accurate prediction to almost all experimental data sets than does the original transform. © 2002 John Wiley & Sons, Inc. Col Res Appl, 27, 49–58, 2002 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Color Research & Application Wiley

CMC 2000 chromatic adaptation transform: CMCCAT2000

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References (25)

Publisher
Wiley
Copyright
Copyright © 2002 John Wiley & Sons, Inc.
ISSN
0361-2317
eISSN
1520-6378
DOI
10.1002/col.10005
Publisher site
See Article on Publisher Site

Abstract

CMCCAT97 is a chromatic adaptation transform included in CIECAM97s, the CIE 1997 colour appearance model, for describing colour appearance under different viewing conditions and is recommended by the Colour Measurement Committee of the Society of Dyers and Colourists for predicting the degree of colour inconstancy of surface colours. Among the many transforms tested, this transform gave the most accurate predictions to a number of experimental data sets. However, the structure of CMCCAT97 is considered complicated and causes problems when applications require the use of its reverse mode. This article describes a simplified version of CMCCAT97— CMCCAT2000—which not only is significantly simpler and eliminates the problems of reversibility, but also gives a more accurate prediction to almost all experimental data sets than does the original transform. © 2002 John Wiley & Sons, Inc. Col Res Appl, 27, 49–58, 2002

Journal

Color Research & ApplicationWiley

Published: Feb 1, 2002

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