en fr Indian Buffet Process Dictionary Learning : algorithms and applications to image processing Processus du Buffet Indien pour lapprentissage de dictionnaire : algorithmes et applications en traitement dimage. Reportar como inadecuado




en fr Indian Buffet Process Dictionary Learning : algorithms and applications to image processing Processus du Buffet Indien pour lapprentissage de dictionnaire : algorithmes et applications en traitement dimage. - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

1 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 2 Ecole Centrale de Lille

Abstract : Ill-posed inverse problems call for some prior model to define a suitable set of solutions. A wide family of approaches relies on the use of sparse representations. Dictionary learning precisely permits to learn a redundant set of atoms to represent the data in a sparse manner. Various approaches have been proposed, mostly based on optimization methods. We propose a Bayesian non parametric approach called IBP-DL that uses an Indian Buffet Process prior. This method yields an efficient dictionary with an adaptive number of atoms. Moreover the noise and sparsity levels are also inferred so that no parameter tuning is needed. We elaborate on the IBP-DL model to propose a model for linear inverse problems such as inpainting and compressive sensing beyond basic denoising. We derive a collapsed and an accelerated Gibbs samplers and propose a marginal maximum a posteriori estimator of the dictionary. Several image processing experiments are presented and compared to other approaches for illustration.

Keywords : sparse representations dictionary learning inverse problems Indian Buffet Process Bayesian non parametric





Autor: Hong-Phuong Dang - Pierre Chainais -

Fuente: https://hal.archives-ouvertes.fr/



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