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Predicting color matches from luminance matches
Author(s) -
Kassandra R. Lee,
Alex Richardson,
Eric Walowit,
Michael A. Crognale,
Michael A. Webster
Publication year - 2020
Publication title -
journal of the optical society of america. a, optics, image science, and vision./journal of the optical society of america. a, online
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.803
H-Index - 158
eISSN - 1520-8532
pISSN - 1084-7529
DOI - 10.1364/josaa.381256
Subject(s) - luminance , observer (physics) , artificial intelligence , computer science , computer vision , sensitivity (control systems) , mathematics , physics , quantum mechanics , electronic engineering , engineering
Color vision and spectral sensitivity vary among individuals with normal color vision; thus, for many applications, it is important to measure and correct for an observer's sensitivity. Full correction would require measuring color and luminance matches and is rarely implemented. However, luminance matches (equiluminance settings) are routinely measured and simple to conduct. We modeled how well an observer's color matches could be approximated by measuring only luminance sensitivity, since both depend on a common set of factors. We show that lens and macular pigment density and $L/M$L/M cone ratios alter equiluminance settings in different ways and can therefore be estimated from the settings. In turn, the density variations can account for a large proportion of the normal variation in color matching. Thus, luminance matches may provide a simple method to at least partially predict an observer's color matches without requiring more complex tasks or equipment.

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