CIE-XYZ fitting by multispectral images and mean square error minimization with a linear interpolation function

Authors

  • J. Conde
  • H. Haneishi
  • M. Yamaguchi
  • N. Oh
  • ama.
  • J. Baez

Keywords:

Multispectral images, CIE-XYZ tristimulus values fitting, interpolation function, mean square error minimization, color difference

Abstract

We present a proposal to achieve accurate color reproduction by fitting the CIE-XYZ tristimulus values of a given color stimulus, and using the 16-band multispectral images, as well as the CIE-XYZ tristimulus values of a known color test chart. We propose a simple linear combination of the multispectral images as interpolation function, which is equivalent to fitting the data to a straight line in a 16-dimentional space. By using this interpolation function, we minimize the merit function of the mean error between the measured and estimated CIE-XYZ tristimulus values of the color test chart. We show, by making a visual comparison between the results achieved using this proposal and the results achieved using a spectral reflectance estimation technique, that the proposed interpolation function when using 16-channel multispectral images produces high quality results in terms of color reproduction fidelity.

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Published

2004-01-01

How to Cite

[1]
J. Conde, H. Haneishi, M. Yamaguchi, N. Oh, ama., and J. Baez, “CIE-XYZ fitting by multispectral images and mean square error minimization with a linear interpolation function”, Rev. Mex. Fís., vol. 50, no. 6, pp. 601–0, Jan. 2004.