Refined filtering of interferometric phase from INSAR data

Radar interferometry has been widely applied in measuring the surface height. The information about surface can be derived from phase interferograms. However, phase noise reduces the accuracy and reliability of that information. Hence, the minimization of phase noise is essential to the retrieval of surface information. This work presents a refined filter that is based on the Lee adaptive INSAR filter and the sigma filter. The basic idea is to filter adaptively the interferometric phase according to the local noise level to minimize the loss of signal for a particular shape of fringes, including in such extreme cases as involve broken fringes, following the elimination of unreliable pixels of phase noise. The goal is to reduce the phase deviation and the number of residues, and minimize the phase error. The proposed filter was inspected herein using both simulated data and real interferometer data. Results reveal that the filtering performance is better than that of commonly used filters.