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LEUKOS
The Journal of the Illuminating Engineering Society
Volume 12, 2016 - Issue 1-2: Special Issue on Color Rendition
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Articles

Why Color Space Uniformity and Sample Set Spectral Uniformity Are Essential for Color Rendering Measures

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Pages 39-50 | Received 11 Aug 2015, Accepted 03 Sep 2015, Published online: 12 Oct 2015
 

ABSTRACT

Recently, a group including the present authors developed a new color rendering (fidelity) measure, approved by the IES and henceforth referred to as IES Rf, that has two major updates with respect to the general color rendering index Ra of the CIE. First, it proposes an update to the more perceptually uniform CAM02-UCS color space. Secondly, instead of using only a small number (eight) of moderately saturated samples to determine a general color fidelity index, the IES method proposes using a set of 99 samples uniformly distributed in color space. In addition to the latter, the sample set has one other important property: spectral uniformity. This ensures that the sample set is not wavelength biased: all wavelengths contribute equivalently to the general color fidelity score. This article explores the importance of these two updates for color fidelity evaluation. It shows how the color space update results in a substantial spread of the new color fidelity scores relative to the old CIE Ra values and how the sample set update results in an overall reduction of color fidelity scores for most light source spectra with high CIE Ra (≥80) and high luminous efficacy of radiation (LER) values, especially those with narrowband or spiked spectral features. It is shown that calculated color fidelity scores are affected by the degree of sample set spectral uniformity and that, in the absence of sample set spectral uniformity, light source spectra can be tuned to yield anomalously high CIE Ra values without necessarily yielding an increase in actual perceived color fidelity.

Notes

1. 1.A color space is perceptually uniform if the distance between any two colors is proportional to their perceived dissimilarity.

Additional information

Funding

Kevin Smet was supported by a Postdoctoral Fellowship of the Research Foundation Flanders (12B4913N and 12B4916N).

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