A spectral theory of color perception.
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.
Clark
James J
JJ
Centre for Intelligent Machines, McGill University, 3480 University Street, Montreal, Quebec, Canada. clark@cim.mcgill.ca
Skaff
Sandra
S