An EM approach for Poisson-Gaussian noise modeling - Signal and communications Accéder directement au contenu
Communication Dans Un Congrès Année : 2011

An EM approach for Poisson-Gaussian noise modeling

Résumé

This paper deals with noise parameter estimation. We assume observations corrupted by noise modelled as a sum of two random processes: one Poisson and the other a (nonzero mean) Gaussian. Such problems arise in various applications, e.g. in astronomy and confocal microscopy imaging. To estimate noise parameters, we propose an iterative algorithm based on an Expectation-Maximization approach. This allows us to jointly estimate the scale parameter of the Poisson component and the mean and variance of the Gaussian one. Moreover, an adequate initialization based on cumulants is provided. Numerical difficulties arising from the procedure are also addressed. To validate the proposed method in terms of accuracy and robustness, tests are performed on synthetic data. The good performance of the method is also demonstrated in a denoising experiment on real data.
Fichier principal
Vignette du fichier
Jezierska_2011_eusipco.pdf (102.56 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00733633 , version 1 (19-09-2012)

Identifiants

  • HAL Id : hal-00733633 , version 1

Citer

Anna Jezierska, Caroline Chaux, Jean-Christophe Pesquet, Hugues Talbot. An EM approach for Poisson-Gaussian noise modeling. EUSIPCO 2011, Aug 2011, Barcelona, Spain. pp.2244-2248. ⟨hal-00733633⟩
158 Consultations
256 Téléchargements

Partager

Gmail Facebook X LinkedIn More