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Volume: 29 | Article ID: art00060
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Testing Colour Appearance Model Based UCS Using HDR, WCG and COMBVD Datasets
Xu Qiang
Muhammad Safdar
Ming Ronnier Luo
  DOI :  10.2352/issn.2169-2629.2021.29.381  Published Online :  November 2021
Abstract

Two colour appearance models based UCSs, CAM16-UCS and ZCAM-QMh, were tested using HDR, WCG and COMBVD datasets. As a comparison, two widely used UCSs, CIELAB and ICTCP, were tested. Metrics of the STRESS and correlation coefficient between predicted colour differences and visual differences, together with local and global uniformity based on their chromatic discrimination ellipses, were applied to test models' performance. The two UCSs give similar performance. The luminance parametric factor kL, and power factor γ, were introduced to optimize colour-difference models. Factors kL and γ of 0.75 and 0.5, gave marked improvement to predict the HDR dataset. Factor kL of 0.3 gave significant improvement in the test of WCG dataset. In the test of COMBVD dataset, optimization provide very limited improvement.

Journal Title : Color and Imaging Conference
Publisher Name : Society for Imaging Science and Technology
Publisher Location : 7003 Kilworth Lane, Springfield, VA 22151 USA
Subject Areas :
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 DOI 10.2352/issn.2169-2629.2021.29.381
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Xu Qiang, Muhammad Safdar, Ming Ronnier Luo, "Testing Colour Appearance Model Based UCS Using HDR, WCG and COMBVD Datasets"  in Proc. IS&T 29th Color and Imaging Conf.,  2021,  pp 381 - 386,  https://doi.org/10.2352/issn.2169-2629.2021.29.381

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Copyright © Society for Imaging Science and Technology 2021
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Color and Imaging Conference
color imaging conf
2166-9635
Society for Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151 USA
10.2352/issn.2169-2629.2021.29.381
2166-9635(20211101)2021:29L.381;1-
cic_21669635_v2021n29_input/s60.xml
/ist/cic/2021/00002021/00000029/art00060
Articles
Testing Colour Appearance Model Based UCS Using HDR, WCG and COMBVD Datasets
QiangXu
SafdarMuhammad
Ronnier LuoMing
01112021
2021
29
381
386
2021
Two colour appearance models based UCSs, CAM16-UCS and ZCAM-QMh, were tested using HDR, WCG and COMBVD datasets. As a comparison, two widely used UCSs, CIELAB and ICTCP, were tested. Metrics of the STRESS and correlation coefficient between predicted colour differences and visual differences, together with local and global uniformity based on their chromatic discrimination ellipses, were applied to test models' performance. The two UCSs give similar performance. The luminance parametric factor kL, and power factor γ, were introduced to optimize colour-difference models. Factors kL and γ of 0.75 and 0.5, gave marked improvement to predict the HDR dataset. Factor kL of 0.3 gave significant improvement in the test of WCG dataset. In the test of COMBVD dataset, optimization provide very limited improvement.
colour appearance modeluniform colou spaceHDRWCG