MRF model based approach for simultaneous InSAR phase filtering and unwrapping

This paper presents a new integrated InSAR phase filtering and unwrapping method based on a Markov Random Field model. This approach aims to estimate the noise free unwrapped phase from the observed noisy interferogram. The phase image is modeled using MRF where the correponding energy function is defined. This fuctional contains two parts: the first part is dedicated to the interferogram filtering process and the goal of the second part is to unwrap this filtered phase. The filtered unwrapped phase image is estimated by minimising the proposed energy function. In this paper, we used the genetic algorithm to attempt this minimum. The proposed approach is tested and validated on simulated and real interferograms generated from Envisat satellite acquired over the region of Mahdia in Tunisia.