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2 April 2013 Principal wavelengths in the formation of spectral images of natural scenes
Francisco J. Sanchez-Marin
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Journal of Biomedical Optics, Vol. 18, Issue 4, 046005 (April 2013). https://doi.org/10.1117/1.JBO.18.4.046005
Abstract
Considering the high degree of correlation in the visible spectrum, the principal wavelengths from spectral measurements of radiance recorded in spectral images were selected using a method based on principal components analysis (PCA). It seems to be that this is the first time that, instead of using spectra, data is taken directly from the “slices” of spectral images; the method has the advantage of preserving the structure of the original data in the reduced data set. A “true” dimensionality of five wavelengths resulted for all the analyzed images. The averages of the selected wavelengths for 10 spectral images produced good results for a human observer. These results were possible using only four wavelengths. Though PCA by itself is not able to include the impact of specific sensors on the selection of basis functions, results suggest that the variable selection method used in this work (which is not just PCA) yielded objective information of the structure of the physical stimuli (i.e., the spectral structures) that have been shaping the visual systems of animals and insects since many years ago.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
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Francisco J. Sanchez-Marin "Principal wavelengths in the formation of spectral images of natural scenes," Journal of Biomedical Optics 18(4), 046005 (2 April 2013). https://doi.org/10.1117/1.JBO.18.4.046005
Published: 2 April 2013
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KEYWORDS
Principal component analysis
RGB color model
Visible radiation
Feature selection
Cameras
Image analysis
Color vision
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