A MAP Approach With Huber-MRF for Synthetic Aperture Interferometric Radiometer

Reconstructing the brightness temperature map from the visibilities in synthetic aperture interferometric radiometers (SAIRs) has been proved to be an ill-posed inverse problem. The regularization methods are crucial to effectively overcome the ill-condition of the inverse problem. This letter presents a maximum a posteriori (MAP) approach for retrieving the accurate brightness temperature map in SAIRs. Furthermore, edge-preserving regularization using a Huber-Markov random field (Huber-MRF) model is used to provide a stable solution and eliminate the oscillation artifacts. Numerical experiment results and quantitative analyses verify the effectiveness of the proposed method.