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Proceedings Paper

Spectral BRDF modeling using wavelets
Author(s): Luc Claustres; Yannick Boucher; Mathias Paulin
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Paper Abstract

The Bi-directional Reflectance Distribution Function (BRDF) is a complex function characterizing the reflection of light on a surface. It depends on five variables: four angles (lighting direction and observer direction) and the wavelength. A complete measurement campaign generates a large data set difficult to model. One way to proceed is to fit an analytical model on this data set. A numerical optimization technique, like simplex, allows to retrieve the best parameters of the model by minimizing the error with regard to measurements. Most of the analytical models obtain poor results for specular surfaces, and no wavelength dependent model actually exists. These reasons lead us to choose a numerical approach and particularly wavelets. This paper shows how wavelets can be used to provide an efficient BRDF model. Results of modeling are presented over a large collection of measurement data sets. At fixed wavelength, wavelet model has pretty good results, comparable to the best analytical models for diffuse surfaces, and much better for specular surfaces. The global relative error is lower than 5% with a compression ratio better than 90%. For spectral data sets, the wavelet model also presents very interesting performances with compression ratios greater than 95% and error lower than 2%.

Paper Details

Date Published: 8 March 2002
PDF: 11 pages
Proc. SPIE 4738, Wavelet and Independent Component Analysis Applications IX, (8 March 2002); doi: 10.1117/12.458726
Show Author Affiliations
Luc Claustres, IRIT-Univ. Paul Sabatier and ONERA-CERT (France)
Yannick Boucher, ONERA-CERT (France)
Mathias Paulin, IRIT-Univ. Paul Sabatier (France)

Published in SPIE Proceedings Vol. 4738:
Wavelet and Independent Component Analysis Applications IX
Harold H. Szu; James R. Buss, Editor(s)

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