Abstract

The paper adopts the philosophical stance that colors are real and can be identified with spectral models based on the photoreceptor signals. A statistical setting represents spectral profiles as probability density functions. This permits the use of analytic tools from the field of information geometry to determine a new kind of color space and structure deriving therefrom. In particular, the metric of the color space is shown to be the Fisher information matrix. A maximum entropy technique for spectral modeling is proposed that takes into account measurement noise. Theoretical predictions provided by our approach are compared with empirical colorfulness and color similarity data.

© 2009 Optical Society of America

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History
Original Manuscript: February 17, 2009
Manuscript Accepted: September 29, 2009
Revised Manuscript: September 17, 2009
Published: November 4, 2009

References

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Author Affiliations

James J. Clark, Sandra Skaff

McGill University

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