A computational strategy exploiting genetic algorithms to recover color surface reflectance functions

  • Authors:

  • Raimondo Schettini;Silvia Zuffi

  • Affiliations:

  • DISCo (Dipartimento di Informatica, Sistemistica e Comunicazione), Università degli Studi di Milano-Bicocca, Via Bicocca degli Arcimboldi, 8, 20126, Milan, Italy;Construction Technologies Institute, ITC-CNR, Via Bassini 15, 20133, Milan, Italy

  • Venue:
  • Neural Computing and Applications
  • Year:
  • 2006

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Abstract

Information about the spectral reflectance of a color surface is useful in many applications. Assuming that reflectance functions can be adequately approximated 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 investigated, 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 reflectance spectra.