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A Physically‐based Appearance Model for Special Effect Pigments
Author(s) -
Guo Jie,
Chen Yanjun,
Guo Yanwen,
Pan Jingui
Publication year - 2018
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.13476
Subject(s) - bidirectional reflectance distribution function , iridescence , computer science , precomputation , gaussian , scale (ratio) , reflectivity , optics , interference (communication) , pixel , limit (mathematics) , biological system , computer graphics (images) , computer vision , mathematics , algorithm , physics , mathematical analysis , quantum mechanics , computation , biology , computer network , channel (broadcasting)
An appearance model for materials adhered with massive collections of special effect pigments has to take both high‐frequency spatial details (e.g., glints) and wave‐optical effects (e.g., iridescence) due to thin‐film interference into account. However, either phenomenon is challenging to characterize and simulate in a physically accurate way. Capturing these fascinating effects in a unified framework is even harder as the normal distribution function and the reflectance term are highly correlated and cannot be treated separately. In this paper, we propose a multi‐scale BRDF model for reproducing the main visual effects generated by the discrete assembly of special effect pigments, enabling a smooth transition from fine‐scale surface details to large‐scale iridescent patterns. We demonstrate that the wavelength‐dependent reflectance inside the pixel's footprint follows a Gaussian distribution according to the central limit theorem, and is closely related to the distribution of the thin‐film's thickness. We efficiently determine the mean and the variance of this Gaussian distribution for each pixel whose closed‐form expressions can be derived by assuming that the thin‐film's thickness is uniformly distributed. To validate its effectiveness, the proposed model is compared against some previous methods and photographs of actual materials. Furthermore, since our method does not require any scene‐dependent precomputation, the distribution of thickness is allowed to be spatially‐varying.