Spatial intra-prediction based on mixtures of sparse representations

Angélique Drémeau 1 Mehmet Türkan 1 Cédric Herzet 1 Christine Guillemot 1 Jean-Jacques Fuchs 1
1 TEMICS - Digital image processing, modeling and communication
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : In this paper, we consider the problem of spatial prediction based on sparse representations. Several algorithms dealing with this problem can be found in the literature. We propose a novel method involving a mixture of sparse representations. We first place this approach into a probabilistic framework and then derive a practical procedure to solve it. Comparisons of the rate-distortion performance show the superiority of the proposed algorithm with regard to other state-of-the-art algorithms.
Type de document :
Communication dans un congrès
Proc. IEEE International Workshop on Multimedia Signal Processing (MMSP), Oct 2010, Saint Malo, France. 2010
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https://hal.inria.fr/inria-00539118
Contributeur : Angélique Drémeau <>
Soumis le : mercredi 24 novembre 2010 - 09:47:58
Dernière modification le : mercredi 16 mai 2018 - 11:23:05

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  • HAL Id : inria-00539118, version 1

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Angélique Drémeau, Mehmet Türkan, Cédric Herzet, Christine Guillemot, Jean-Jacques Fuchs. Spatial intra-prediction based on mixtures of sparse representations. Proc. IEEE International Workshop on Multimedia Signal Processing (MMSP), Oct 2010, Saint Malo, France. 2010. 〈inria-00539118〉

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