A Variational Bayesian Approach for Restoring Data Corrupted with Non-Gaussian Noise

Abstract : In this paper, a methodology is investigated for signal recovery in the presence of non-Gaussian noise. In contrast with regularized minimization approaches often adopted in the literature, in our algorithm the regularization parameter is reliably estimated from the observations. As the posterior density of the unknown parameters is analytically intractable, the estimation problem is derived in a variational Bayesian framework where the goal is to provide a good approximation to the posterior distribution in order to compute posterior mean estimates. Moreover, a majorization technique is employed to circumvent the difficulties raised by the intricate forms of the non-Gaussian likelihood and of the prior density. We demonstrate the potential of the proposed approach through comparisons with state-of-the-art techniques that are specifically tailored to signal recovery in the presence of mixed Poisson-Gaussian noise. Results show that the proposed approach is efficient and achieves performance comparable with other methods where the regularization parameter is manually tuned from an available ground truth.
Type de document :
Rapport
[Research Report] Laboratoire Informatique Gaspard Monge. 2016
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01418399
Contributeur : Emilie Chouzenoux <>
Soumis le : vendredi 16 décembre 2016 - 16:42:48
Dernière modification le : samedi 18 février 2017 - 01:14:50
Document(s) archivé(s) le : mardi 21 mars 2017 - 06:58:28

Fichier

VBA_ARXIV.pdf
Fichiers produits par l'(les) auteur(s)

Licence


Domaine public

Identifiants

  • HAL Id : hal-01418399, version 1

Citation

Yosra Marnissi, Yuling Zheng, Emilie Chouzenoux, Jean-Christophe Pesquet. A Variational Bayesian Approach for Restoring Data Corrupted with Non-Gaussian Noise. [Research Report] Laboratoire Informatique Gaspard Monge. 2016. <hal-01418399>

Partager

Métriques

Consultations de
la notice

197

Téléchargements du document

21