Texture Reconstruction guided by the Histogram of a High-Resolution patch

Abstract : 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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IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2017, 26 (2), pp.549-560
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Contributeur : Mireille El Gheche <>
Soumis le : lundi 23 janvier 2017 - 15:48:12
Dernière modification le : samedi 28 janvier 2017 - 01:03:49

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  • HAL Id : hal-01276582, version 2

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Mireille El Gheche, Jean-François Aujol, Yannick Berthoumieu, Charles-Alban Deledalle. Texture Reconstruction guided by the Histogram of a High-Resolution patch. IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2017, 26 (2), pp.549-560. <hal-01276582v2>

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