Skip to Main content Skip to Navigation
Conference papers

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.
Complete list of metadata

https://hal.inria.fr/inria-00539118
Contributor : Angélique Drémeau <>
Submitted on : Wednesday, November 24, 2010 - 9:47:58 AM
Last modification on : Tuesday, June 15, 2021 - 4:27:45 PM

Identifiers

  • HAL Id : inria-00539118, version 1

Citation

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. ⟨inria-00539118⟩

Share

Metrics

Record views

276