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Volume: 4 | Article ID: art00112
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Supervised training sample selection for the estimation of spectral reflectance using a RGB camera
  DOI :  10.2352/CGIV.2008.4.1.art00112  Published OnlineJanuary 2008
Abstract

Spectral imaging can provide spectral information from which spectral radiance or reflectance can be recovered at each image pixel. Recovery algorithms lead to good spectral and colorimetric performance by directly transforming RGB digital counts to spectral reflectances, but his approach is sensitive to the size and composition of the training set. What we propose here is a supervised method to select the most appropriate samples from a training database to buld the transformation matrix relating digital counts to spectral reflectances. Thus, this approach is tested with real images.

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Clara Plata, Eva M. Valero, Juan L. Nieves, Javier Romero, "Supervised training sample selection for the estimation of spectral reflectance using a RGB camerain Proc. IS&T CGIV 2008/MCS'08 4th European Conf. on Colour in Graphics, Imaging, and Vision 10th Int'l Symp. on Multispectral Colour Science,  2008,  pp 519 - 522,  https://doi.org/10.2352/CGIV.2008.4.1.art00112

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Copyright © Society for Imaging Science and Technology 2008
72010351
Conference on Colour in Graphics, Imaging, and Vision
conf colour graph imag vis
2158-6330
Society of Imaging Science and Technology
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