Accurate and Efficient Filtering using Anisotropic Filter Decomposition

Cyril Soler 1, * Mahdi Bagher 2 Derek Nowrouzezahrai 3
* Corresponding author
1 MAVERICK - Models and Algorithms for Visualization and Rendering
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
3 LIGUM, Dept. I.R.O.
DIRO - Département d'Informatique et de Recherche Opérationnelle [Montreal]
Abstract : Efficient filtering remains an important challenge in computer graphics, particularly when filters are spatially-varying, have large extent, and/or exhibit complex anisotropic profiles. We present an efficient filtering approach for these difficult cases based on anisotropic filter decomposition (IFD). By decomposing complex filters into linear combinations of simpler, displaced isotropic kernels, and precomputing a compact prefiltered dataset, we are able to interactively apply any number of---potentially transformed---filters to a signal. Our performance scales linearly with the size of the decomposition, not the size nor the dimensionality of the filter, and our prefiltered data requires reasonnable storage, comparing favorably to the state-of-the-art. We apply IFD to interesting problems in image processing and realistic rendering.
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Cyril Soler, Mahdi Bagher, Derek Nowrouzezahrai. Accurate and Efficient Filtering using Anisotropic Filter Decomposition. [Research Report] RR-8349, INRIA. 2013, pp.22. ⟨hal-00854193⟩

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