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Various chromatic‐adaptation transformations tested using new colour appearance data in textiles
Author(s) -
Kuo WenGuey,
Luo M. Ronnier,
Bez Helmut E.
Publication year - 1995
Publication title -
color research and application
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.393
H-Index - 62
eISSN - 1520-6378
pISSN - 0361-2317
DOI - 10.1002/col.5080200509
Subject(s) - gamut , chromatic adaptation , colour difference , mathematics , chromatic scale , observer (physics) , adaptation (eye) , transformation (genetics) , color difference , set (abstract data type) , grid , rgb color model , artificial intelligence , statistics , computer science , computer vision , optics , geometry , combinatorics , enhanced data rates for gsm evolution , biochemistry , chemistry , physics , quantum mechanics , gene , programming language
A new set of colour appearance data was obtained from a series of experiments in which 240 wool samples having a large size of 3 x 3 in. square that subtends 10° at the observer's eye, and covering a large colour gamut were used. Each colour was assessed by a panel of five observers using a magnitude estimation method under three light sources, D65, TL84, and A. In total, 10,770 estimations were made, and these form a set of new colour appearance data in textiles. Data analysis was carried out and shows that the accuracy of the visual results for different observers is quite good. the colour appearance data were used to test the performance of seven chromatic‐adaptation transformations, i.e., BFD, Bartleson, von Kries, CIE, Hunt, CIEL*a*b*, and Fairchild. the results show that the BFD transformation gives the most accurate prediction to the visual results between all transformations studied. All transformations can have a better fit to the experimental grid under TL84 than that under A. However, the results given by the best chromatic‐adaptation transformation are still unsatisfied in colour industries, especially in the textile industry. the two sets of experimental grids respectively derived from this work and by Luo et al. (1991) were also studied. an expected difference between the two sets of experimental grids was found. the difference may mainly result from two factors: the experimental method in assessment and the size of the samples. © 1995 John Wiley & Sons, Inc.