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The Theory of the Maximum Visual Efficiency of Colored Materials

MacAdam, David L.·1935·Journal of the Optical Society of America

Abstract

The term “visual efficiency” is used here to represent interchangeably the concepts of visual transmission factors of filters and of visual reflection factors of reflecting surfaces. Fluorescent substances are excluded from consideration. A material exhibits hue because visible radiation in some wavelength bands is more or less completely absorbed. This partial absorption of incident energy, necessary for the appearance of hue, obviously decreases the visual efficiency below the unit efficiency characteristic of a nonabsorbing, hueless, white material. Of all the conceivable spectrophotometric curves of materials exhibiting a given chromaticity when illuminated with light of a specified quality, there must be at least one which yields a maximum value for the visual efficiency. This paper describes the general type of spectrophotometric curve which is known to have this unique property. A new proof of the validity and uniqueness of this type of curve is presented. This proof takes advantage of the simplifications made available by the adoption of the I. C. I. 1931 coordinate system for colorimetry.

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Metadata

Authors
MacAdam, D. L.
Venue
Journal of the Optical Society of America
Published
1935-08-01
Volume
25
Issue
8
Pages
249
ISSN
0030-3941 (ISSN-L)
OpenAlex
W1980671260
Cited by
164
References
0
FWCI
3.31
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Theory of the Maximum Visual Efficiency of Colored Materials. https://app.cochat.ai/papers/10.1364/josa.25.000249
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MacAdam, D. L. (1935). The Theory of the Maximum Visual Efficiency of Colored Materials. Journal of the Optical Society of America. https://doi.org/10.1364/josa.25.000249

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.