You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
27 March 2015Predictive rendering of composite materials: a multi-scale approach
Predictive rendering of material appearance means going deep into the understanding of the physical interaction between light and matter and how these interactions are perceived by the human brain. In this paper we describe our approach to predict the appearance of composite materials by relying on the multi-scale nature of the involved phenomena. Using recent works on physical modeling of complex materials, we show how to predict the aspect of a composite material based on its composition and its morphology. Specifically, we focus on the materials whose morphological structures are defined at several embedded scales. We rely on the assumption that when the inclusions in a composite material are smaller than the considered wavelength, the optical constants of the corresponding effective media can be computed by a homogenization process (or analytically for special cases) to be used into the Fresnel formulas.
The alert did not successfully save. Please try again later.
T. Muller, Patrick Callet, F. da Graça, A. Paljic, P. Porral, R. Hoarau, "Predictive rendering of composite materials: a multi-scale approach," Proc. SPIE 9398, Measuring, Modeling, and Reproducing Material Appearance 2015, 939804 (27 March 2015); https://doi.org/10.1117/12.2077920