Geometric Estimation with Orthogonal Bandlet Bases

Abstract : This article presents the first adaptive quasi minimax estimator for geometrically regular images in the white noise model. This estimator is computed using a thresholding in an adapted orthogonal bandlet basis optimized for the noisy observed image. In order to analyze the quadratic risk of this best basis denoising, the thresholding in an orthogonal bandlets basis is recasted as a model selection process. The resulting estimator is computed with a fast algorithm whose theoretical performance can be derived. This efficiency is confirmed through numerical experiments on natural images.
Type de document :
Communication dans un congrès
Dimitri Van De Ville, Vivek K. Goyal, Manos Papadakis. SPIE Wavelets XII, Aug 2007, San Diego, CA, United States. SPIE, 6701 (2), pp.67010M.1-67010M.10, 2007, SPIE
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Dernière modification le : jeudi 12 avril 2018 - 01:47:35
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  • HAL Id : hal-00365606, version 1

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Gabriel Peyré, Erwan Le Pennec, Charles Dossal, Stéphane Mallat. Geometric Estimation with Orthogonal Bandlet Bases. Dimitri Van De Ville, Vivek K. Goyal, Manos Papadakis. SPIE Wavelets XII, Aug 2007, San Diego, CA, United States. SPIE, 6701 (2), pp.67010M.1-67010M.10, 2007, SPIE. 〈hal-00365606〉

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