A Modification to the Complex-Valued MRF Modeling Filter of Interferometric SAR Phase

This letter focuses on a modified complex-valued Markov random field (CMRF) modeling filter to improve the performance in the filtering of the synthetic aperture radar interferometric phase. In the reference CMRF modeling phase map filter, the CMRF model was employed to update residues and their neighbors. By this, the residues were reduced, and phase jumps were preserved simultaneously. However, residue reduction was still insufficient. Furthermore, incorrect model parameter estimation leads to wrong filtering in some blocks. To solve the two aforementioned problems, we propose a modified CMRF modeling filter, where the original interferogram is divided into overlapped blocks. In addition, the adaptive weighted neighbor values are used to estimate the CMRF model parameters. Both simulated and real data experiments are performed to validate this method.