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Tuning color and saving energy with spatially variable laser illumination
Author(s) -
Jingjing Zhang,
Kevin Smet,
Youri Meuret
Publication year - 2019
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.27.027136
Subject(s) - gamut , color rendering index , optics , projector , spectral color , rendering (computer graphics) , spectral power distribution , laser , hue , radiant energy , hyperspectral imaging , radiant flux , color difference , color space , artificial intelligence , computer science , computer vision , physics , color model , radiation , light emitting diode , enhanced data rates for gsm evolution , image (mathematics)
Previous studies have shown that the radiant flux that needs to be emitted by an illumination system, can be significantly reduced by optimizing its spectral power distribution to the object reflectance spectra, without inducing perceptible chroma or hue shifts of the illuminated objects. In this paper, the idea is explored to vary the spectral power distribution at different positions in the illuminated scene, in order to tailor the color appearance of objects. For this, a spatially variable, laser diode based illumination system is considered with three primaries and large color gamut. The color rendering performance of the illumination system is quantified via the IES TM-30-2018 method. It is shown that it is possible to reach the maximal color gamut score that is theoretically allowed by the corresponding color fidelity score. This is a unique property of an illumination system with a spatially variable spectral power distribution. The radiant flux requirements of this laser diode based illumination system are theoretically investigated for various color rendering settings, showing reduced power requirements for higher color gamut. The possibility to tune color rendering is also experimentally demonstrated with a set-up that consists of a commercially available laser projector with a hyperspectral camera. By including a feedback optimization algorithm, it is possible to reach the targeted color rendering performance.

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