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A Monte Carlo method for assessing color rendering quality with possible application to color rendering standards
Author(s) -
Whitehead Lorne A.,
Mossman Michele A.
Publication year - 2012
Publication title -
color research and application
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.393
H-Index - 62
eISSN - 1520-6378
pISSN - 0361-2317
DOI - 10.1002/col.20649
Subject(s) - color rendering index , rendering (computer graphics) , computer science , high color , spectral power distribution , color temperature , artificial intelligence , color difference , monte carlo method , rgb color model , computer vision , statistics , mathematics , light emitting diode , optics , color image , image processing , physics , enhanced data rates for gsm evolution , image (mathematics)
The lighting industry has been increasingly challenged to reduce electrical energy consumption while providing illumination with sufficient color rendering quality. As a result, the problem of accurately assessing color rendering quality has gained increased prominence and the introduction of efficient narrow band light emitting diode (LED) sources has further intensified the debate. This study argues that there is a basic problem with the traditional method of quantifying color quality color rendering index (CRI), one that cannot be solved through minor improvements. The CRI relies on a determination of the degree of color distortion that a test source produces for a small number of test samples of specified spectral reflectance distribution, but there is no clear objective rationale for selecting these few samples. Also, any such arbitrary scoring scheme lacks an objective argument for what constitutes an acceptable score. This study proposes a new method for color rendering assessment that determines the color shift of one thousand, or more, representative reflection spectra that span the full multidimensional range of possible spectral distributions and colors. This broad sampling eliminates the intrinsic selection bias of the CRI calculation and its variants and it is compatible with a more objective standard for a color quality score, one that is statistically based on the fraction of the test spectra that experience color shifts that are less than a just noticeable difference (JND), or an agreed upon multiple of it. Since the concept of JNDs in color has been reproducibly quantified, it is hoped that this approach will be widely acceptable. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2012