Locally Parallel Texture Modeling - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles SIAM Journal on Imaging Sciences Year : 2011

Locally Parallel Texture Modeling


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.
Fichier principal
Vignette du fichier
MaurelAujolPeyre-SIIS.pdf (4.06 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

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



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⟩
984 View
567 Download



Gmail Facebook X LinkedIn More