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Spectral spaces and color spaces
Author(s) -
Ramanath Rajeev,
Kuehni Rolf G.,
Snyder Wesley E.,
Hinks David
Publication year - 2004
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.10211
Subject(s) - color space , mathematics , object (grammar) , dimensionality reduction , space (punctuation) , curse of dimensionality , spectral color , color model , standard illuminant , color difference , artificial intelligence , primary color , pattern recognition (psychology) , computer science , image (mathematics) , enhanced data rates for gsm evolution , operating system
It has long been known that color experiences under controlled conditions may be ordered into a color space based on three primary attributes. It is also known that the color of an object depends on its spectral reflectance function, among other factors. Using dimensionality reduction techniques applied to reflectance measurements (in our case a published set of 1 nm interval reflectance functions of Munsell color chips) it is possible to construct 3D spaces of various kinds. In this article we compare color spaces, perceptual or based on dimensionality reduction using color matching functions and additional operations (uniform color space), to spectral spaces derived with a variety of dimensionality reduction techniques. Most spectral spaces put object spectra into the ordinal order of a psychological color space, but so do many random continuous functions. In terms of interval scales there are large differences between color and spectral spaces. In spectral spaces psychophysical metamers are located in different places. © 2003 Wiley Periodicals, Inc. Col Res Appl, 29, 29–37, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10211