Titre :

Bayesian Image Restoration under Poisson Noise and Log-concave Prior

Auteur(s) :

Vono, Maxime [Auteur]
Signal et Communications [IRIT-SC]
Dobigeon, Nicolas [Auteur]
Signal et Communications [IRIT-SC]
Institut National Polytechnique (Toulouse) [Toulouse INP]
Chainais, Pierre [Auteur]
Centrale Lille
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Titre de la manifestation scientifique :

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Ville :

Brighton

Pays :

Royaume-Uni

Date de début de la manifestation scientifique :

2019-05-12

Titre de l’ouvrage :

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Éditeur :

IEEE

Mot(s)-clé(s) en anglais :

Bayesian inference
split-and-augmented Gibbs sampler
Poisson noise
image restoration

Discipline(s) HAL :

Informatique [cs]/Traitement du signal et de l'image [eess.SP]

Résumé en anglais : [en]

In recent years, much research has been devoted to the restoration of Poissonian images using optimization-based methods. On the other hand, the derivation of efficient and general fully Bayesian approaches is still an ...
Lire la suite >In recent years, much research has been devoted to the restoration of Poissonian images using optimization-based methods. On the other hand, the derivation of efficient and general fully Bayesian approaches is still an active area of research and especially if standard regularization functions are used, e.g. the total variation (TV) norm. This paper proposes to use the recent split-and-augmented Gibbs sampler (SPA) to sample efficiently from an approximation of the initial target distribution when log-concave prior distributions are used. SPA embeds proximal Markov chain Monte Carlo (MCMC) algorithms to sample from possibly non-smooth log-concave full conditionals. The benefit of the proposed approach is illustrated on several experiments including different regularizers, intensity levels and with both analysis and synthesis approaches.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL