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P‐33: Which Color Gamut Metric Best Predicts Human Display Preference?
Author(s) -
Hillis James M,
Schumacher Jennifer,
Thielen James,
Van Derlofske John,
Wheatley John,
Benoit Gilles,
Lathrop Art
Publication year - 2014
Publication title -
sid symposium digest of technical papers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 44
eISSN - 2168-0159
pISSN - 0097-966X
DOI - 10.1002/j.2168-0159.2014.tb00282.x
Subject(s) - gamut , luminance , computer science , color space , artificial intelligence , colorimetry , metric (unit) , computer vision , color balance , color depth , photometry (optics) , set (abstract data type) , computer graphics (images) , color image , image processing , engineering , operations management , image (mathematics) , programming language , stars
Advances in display technology depend on our ability to develop miniscule elements that emit a broad range of light intensities and colors. Existing technologies are limited and face trade‐offs between producing luminance and color. Photometry and colorimetry provide tools to help developers understand those trade‐offs and to set meaningful targets for the future. Uncertainty remains however as to which metrics provide the best guidelines. We examined the relationship between 8 color metrics and human preferences for displays that differed only in color gamut. We found that (1) volume metrics, computed from display luminance and color capacity, outperformed area metrics computed only from color and (2) of the color metrics we considered, CIECAM′02 saturation best predicted viewer preference.