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Specularity removal from imaging spectroscopy data via entropy minimisation
conference contribution
posted on 2011-12-01, 00:00 authored by L Gu, Antonio Robles-KellyAntonio Robles-KellyIn this paper, we present a method to remove specularities from imaging spectroscopy data. We do this by making use of the dichromatic model so as to cast the problem in a linear regression setting. We do this so as to employ the average radiance for each pixel as a means to map the spectra onto a two-dimensional space. This permits the use of an entropy minimisation approach so as to recover the slope of a line described by a linear regressor. We show how this slope can be used to recover the specular coefficient in the dichromatic model and provide experiments on real-world imaging spectroscopy data. We also provide comparison with an alternative and effect a quantitative analysis that shows our method is robust to changes the degree of specularity of the image or the location of the light source in the scene. © 2011 IEEE.
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Pagination
59 - 65Publisher DOI
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9780769545882Publication classification
E1.1 Full written paper - refereedTitle of proceedings
Proceedings - 2011 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2011Usage metrics
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