A comprehensive test of colour-difference formulae and uniform colour spaces using available visual datasets

被引:15
|
作者
Luo, Ming Ronnier [1 ]
Xu, Qiang [1 ]
Pointer, Michael [2 ]
Melgosa, Manuel [3 ]
Cui, Guihua [4 ]
Li, Changjun [5 ]
Xiao, Kaida [2 ]
Huang, Min [6 ]
机构
[1] Zhejiang Univ, State Key Lab Modern Opt Instrumentat, Hangzhou, Peoples R China
[2] Univ Leeds, Leeds Inst Text & Colour, Leeds, England
[3] Univ Granada, Dept Opt, Granada, Spain
[4] Wenzhou Univ, Coll Elect & Elect Engn, Wenzhou, Peoples R China
[5] Univ Sci & Technol Liaoning, Sch Comp & Software Engn, Anshan, Peoples R China
[6] Beijing Inst G Commun, Printing & Packaging Engn, Beijing, Peoples R China
来源
COLOR RESEARCH AND APPLICATION | 2023年 / 48卷 / 03期
关键词
CAM16-UCS; colour-difference formulae; uniform colour spaces; HIGH DYNAMIC-RANGE; PERFORMANCE; APERTURE;
D O I
10.1002/col.22844
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
The paper describes a comprehensive test to evaluate the performance of current colour-difference models using available experimental datasets. In total, 28 individual datasets were accumulated to test 17 colour-difference formulae, 13 of them based on Uniform Colour Spaces (UCSs) in terms of the Standardized Residual Sum of Squares (STRESS) measure. The 28 datasets were divided into three groups: Large Colour-Difference data (LCD), Small Colour-Difference data for surface colours (SCDs), and Small Colour Difference data for display colours (SCDd). For each colour model, four versions were tested: the original model, and that including k(L)-, Gamma- and k(L)/Gamma, which are the lightness parametric factor, the colour-difference exponent factor, and the combination of both, respectively, optimized to fit particular dataset(s). The statistical F-test was applied to test the difference between each pair of models. Furthermore, parametric effects between the large/small colour-difference magnitudes, and between surface/display colours were investigated. The results showed that CAM16-UCS significantly outperformed the other models for all groups. It accurately predicted all types of data and should be proposed for colour-difference evaluation across all industries.
引用
收藏
页码:267 / 282
页数:16
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