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

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.