Poisson-Gaussian noise parameter estimation in fluorescence microscopy imaging

Anna Jezierska (1) , Hugues Talbot (1) , Caroline Chaux (1) , Jean-Christophe Pesquet (1) , Gilbert Engler (2)

1 LIGM - Laboratoire d'Informatique Gaspard-Monge
2 IBSV - Interactions Biotiques et Santé Végétale

In this paper, we present a new fully automatic approach for noise parameter estimation in the context of fluorescence imaging systems. In particular, we address the problem of Poisson-Gaussian noise modeling in the nonstationary case. In microscopy practice, the nonstationarity is due to the photobleaching effect. The proposed method consists of an adequate moment based initialization followed by Expectation-Maximization iterations. This approach is shown to provide reliable estimates of the mean and the variance of the Gaussian noise and of the scale parameter of Poisson noise, as well as of the photobleaching rates. The algorithm performance is demonstrated on both synthetic and real fluorescence microscopy image sequences.

Mots clés: Noise identification; confocal imaging systems calibration; fluorescence photobleaching; Expectation-Maximization algorithm; image calibration

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Anna Jezierska, Hugues Talbot, Caroline Chaux, Jean-Christophe Pesquet, Gilbert Engler. Poisson-Gaussian noise parameter estimation in fluorescence microscopy imaging. International Symposium on Biomedical Imaging (ISBI), May 2012, Barcelona, Spain. ⟨hal-00646382v2⟩