色域
数学
显色指数
色调
渲染(计算机图形)
人工智能
相关性
色空间
统计
作者
D Hou,Y Ni,Y Wang,C Weirich,H Shen,Yandan Lin
标识
DOI:10.1177/14771535221094277
摘要
This paper investigated colour discrimination based on current available indexes, and predictors were proposed for global and targeted colour scenarios. Thirty participants conducted the Farnsworth–Munsell 100 hue test under 21 lighting conditions. The experiment results revealed that the distribution of total error score (TES) and adjusted total error score (TES adj ) showed arc shapes centred on the optimal point (100, 100) in both R f –R g and colour rendering index–gamut area index coordinate systems. On this basis, global colour discrimination scores, CDS1 and CDS2, based on the colour fidelity and colour gamut characteristics, were proposed. The results demonstrated that both CDS1 ( r = 0.82, p < 0.001) and CDS2 ( r = 0.81, p < 0.001) provided good linear correlations with TES, and CDS1 ( r = 0.75, p < 0.001) and CDS2 ( r = 0.77, p < 0.001) also exhibited a good linear correlation with TES adj . Furthermore, the global colour gamut was divided into four local colour spaces (red–yellow, yellow–green, green–blue and blue–red), and the CDSs in the local gamut (CDS local and CDS adj,local ) were constructed using the local colour properties, including R cs,local , R hs,local and R f,local . The linear regression results demonstrated that CDS local ([Formula: see text]) and CDS adj,local ([Formula: see text]) can be effective colour discrimination predictors for the targeted colour scenarios.
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