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Volume: 2 | Article ID: art00073
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Color Differences in a Spectral Space
  DOI :  10.2352/CGIV.2004.2.1.art00073  Published OnlineJanuary 2004
Abstract

In this study, color similarity metrics in a spectral space are considered. The paper gives a brief overview of several existing measures and presents a novel approach based on kernel methods. New similarity measures for spectral images based upon kernel methods include polynomial, Gaussian radial basis function and sigmoid kernels. The performance of the methods is tested against the Munsell Matte spectral dataset. Kernel methods are compared to twelve well-known similarity metrics, i.e. Correlation Coefficient, Exponential Similarity, Maximum-Minimum methods, etc. Spectral differences of constant Hue, adjacent Values and Chromas have been evaluated using these metrics. The tests show that the proposed Gaussian radial basis function kernel metric performs significantly better, compared to the rest of the measures.

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Diana Kalenova, Pekka Toivanen, Vladimir Botchko, "Color Differences in a Spectral Spacein Proc. IS&T CGIV 2004 Second European Conf. on Colour in Graphics, Imaging, and Vision,  2004,  pp 368 - 371,  https://doi.org/10.2352/CGIV.2004.2.1.art00073

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Copyright © Society for Imaging Science and Technology 2004
72010351
Conference on Colour in Graphics, Imaging, and Vision
conf colour graph imag vis
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