DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2013.102
Eric Heitz , INRIA-LJK (Université de Grenoble and CNRS), Grenoble
Derek Nowrouzezahrai , Université de Montréal, Montreal
Pierre Poulin , Université de Montréal, Montreal
Fabrice Neyret , INRIA-LJK (Université de Grenoble and CNRS), Grenoble
Applying non-linear transfer functions and look-up tables to procedural functions (such as noise), surface attributes, or even surface geometry are common strategies used to enhance visual detail. As with any textured or geometric detail, proper filtering is needed to reduce aliasing when viewed across a range of distances, but accurate and efficient transfer function filtering remains an open problem for several reasons: transfer functions are complex and non-linear, especially when mapped through procedural noise and/or geometry-dependent functions. We accurately solve this problem by computing and sampling from specialized filtering distributions on the fly, yielding very fast performance. We investigate the case where the transfer function to filter is a color map applied to surface textures, as well as color maps applied according to (microscale) geometric details. We introduce a novel representation of a (potentially modulated) color map's distribution over pixel footprints using Gaussian statistics and, in the more complex case of high-resolution color mapped microsurface details, our filtering is view- and light-dependent, and capable of correctly handling masking and occlusion effects. Our approach can be generalized to filter other physical-based rendering quantities. Our framework is also compatible with the case of transfer functions used to warp surface geometry.
Color, Colored noise, Image color analysis, Equations, Geometry, Transfer functions, and texture, Picture/Image Generation, Color, shading, shadowing
D. Nowrouzezahrai, F. Neyret, P. Poulin and E. Heitz, "Filtering Non-Linear Transfer Functions on Surfaces," in IEEE Transactions on Visualization & Computer Graphics.