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Article Dans Une Revue IEEE Transactions on Image Processing Année : 2017

Texture Reconstruction guided by a High-Resolution Patch

Résumé

In this paper, we aim at super-resolving a low-resolution texture under the assumption that a high-resolution patch of the texture is available. To do so, we propose a variational method that combines two approaches, that are texture synthesis and image reconstruction. The resulting objective function holds a nonconvex energy that involves a quadratic distance to the low-resolution image, a histogram-based distance to the high-resolution patch, and a nonlocal regularization that links the missing pixels with the patch pixels. As for the histogram-based measure, we use a sum of Wasserstein distances between the histograms of some linear transformations of the textures. The resulting optimization problem is efficiently solved with a primal-dual proximal method. Experiments show that our method leads to a significant improvement, both visually and numerically, with respect to state-of-the-art algorithms for solving similar problems.
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Dates et versions

hal-01276582 , version 1 (19-02-2016)
hal-01276582 , version 2 (23-01-2017)
hal-01276582 , version 3 (27-07-2020)

Identifiants

Citer

Mireille El Gheche, Jean-François Aujol, Yannick Berthoumieu, Charles-Alban Deledalle. Texture Reconstruction guided by a High-Resolution Patch. IEEE Transactions on Image Processing, 2017, 26 (2), pp.549-560. ⟨10.1109/TIP.2016.2627812⟩. ⟨hal-01276582v3⟩
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