Information about the spectral reflectance of a color surface is useful in many applications. Assuming that reflectance functions can be adequately approxi- mated by a linear combination of a small number of basis functions, we address here the recovery of a surface reflectance function, given the tristimulus values under one or more illuminants. Basis functions presenting different characteristics and cardinalities are investi- gated, and genetic algorithms are employed to optimize the estimation. Our analysis of a variety of standard datasets provides information about the ability of each set of basis functions we used to model generic reflec- tance spectra.
A Computational Strategy Exploiting Genetic Algorithms to Recover Color Surface Reflectance Functions
S Zuffi
2007
Abstract
Information about the spectral reflectance of a color surface is useful in many applications. Assuming that reflectance functions can be adequately approxi- mated by a linear combination of a small number of basis functions, we address here the recovery of a surface reflectance function, given the tristimulus values under one or more illuminants. Basis functions presenting different characteristics and cardinalities are investi- gated, and genetic algorithms are employed to optimize the estimation. Our analysis of a variety of standard datasets provides information about the ability of each set of basis functions we used to model generic reflec- tance spectra.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.