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Article Dans Une Revue SIAM Journal on Imaging Sciences Année : 2011

Locally Parallel Texture Modeling

Résumé

This article presents a new adaptive framework for locally parallel texture modeling. Oscillating patterns are modeled with functionals that constrain the local Fourier decomposition of the texture. We first introduce a texture functional which is a weighted Hilbert norm. The weights on the local Fourier atoms are optimized to match the local orientation and frequency of the texture. This adaptive model is used to solve image processing inverse problems, such as image decomposition and inpainting. The local orientation and frequency of the texture component are adaptively estimated during the minimization process. To improve inpainting performances over large missing regions, we introduce a higly non-convex generalization of our texture model. This new model constrains the amplitude of the texture and it allows one to impose an arbitrary oscillation profile. Numerical results illustrate the effectiveness of the method.
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Dates et versions

hal-00415779 , version 1 (10-09-2009)
hal-00415779 , version 2 (17-01-2011)

Identifiants

Citer

Pierre Maurel, Jean-François Aujol, Gabriel Peyré. Locally Parallel Texture Modeling. SIAM Journal on Imaging Sciences, 2011, 4 (1), pp.413-447. ⟨10.1137/090770795⟩. ⟨hal-00415779v2⟩
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