A Robust EM Algorithm for Radio Interferometric Imaging in The Presence of Outliers

Yassine Mhiri (1) , Mohammed Nabil El Korso (2) , Arnaud Breloy (3, 4) , Pascal Larzabal (1)

1 SATIE - Systèmes et Applications des Technologies de l'Information et de l'Energie
2 L2S - Laboratoire des signaux et systèmes
3 LEME - Laboratoire Energétique Mécanique Electromagnétisme
4 UPN - Université Paris Nanterre

Image synthesis in the context of radio interferometric data can be expressed as a signal reconstruction from incomplete Fourier measurements. Most imaging techniques for radio interferometry lie in minimizing the least square error between the reconstructed image and the observed data assuming an additive white gaussian noise. In this paper, we derive an expectation-maximization based imaging algorithm that handles the presence of outliers in the observed data. Subsequently, we propose a new generic image synthesis algorithm based on the expectation-maximization algorithm, leading to a computationally efficient method.

Keywords: Radioastronomy; expectation-maximization; image restauration

Domains: Signal and Image processing

Yassine Mhiri, Mohammed Nabil El Korso, Arnaud Breloy, Pascal Larzabal. A Robust EM Algorithm for Radio Interferometric Imaging in The Presence of Outliers. SiPS22-IEEE Workshop on Signal Processing Systems, Nov 2022, Rennes, France. pp.1-5, ⟨10.1109/SiPS55645.2022.9919255⟩. ⟨hal-03823295⟩