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Explicit Reconstruction for Image Inpainting

Pierre Kornprobst 1 Gilles Aubert 1
1 ODYSSEE - Computer and biological vision
DI-ENS - Département d'informatique de l'École normale supérieure, CRISAM - Inria Sophia Antipolis - Méditerranée , ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, ENPC - École des Ponts ParisTech
Abstract : Image inpainting refers to techniques which allow to fill in a gap $\Omega$ given the intensities around it. In this paper, we focus on geometric image inpainting for which several PDE based models have been proposed. Most of them rely on a transport or/and a diffusion equation of the intensity inside $\Omega$. The direction of the reconstructed isophotes and the gray levels are generally computed in a coupled way. Instead, we propose in this paper a two step approach. First we estimate the tangents of the missing isophotes using a tensor field diffusion process. Then we simply recover the gray levels by integrating along integral curves of the tensors principal eigenvectors. Such an approach has very few parameters to tune and we illustrate its performance on several synthetic and real examples.
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https://hal.inria.fr/inria-00071360
Contributor : Rapport de Recherche Inria <>
Submitted on : Tuesday, May 23, 2006 - 4:51:47 PM
Last modification on : Wednesday, October 14, 2020 - 4:11:32 AM
Long-term archiving on: : Tuesday, February 22, 2011 - 11:54:54 AM

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  • HAL Id : inria-00071360, version 1

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Pierre Kornprobst, Gilles Aubert. Explicit Reconstruction for Image Inpainting. [Research Report] RR-5905, INRIA. 2006. ⟨inria-00071360⟩

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