A Novel Adaptive InSAR Phase Filtering Method Based on Complexity Factors

Abstract

Phase filtering is an essential step in interferometric synthetic aperture radar (InSAR) imaging. For interferograms of complicated and changeable terrain, the increasing resolution of InSAR images makes it even more difficult. In this paper, a novel adaptive InSAR phase filtering method based on complexity factors is proposed. Firstly, three complexity factors based on the noise distribution and terrain slope information of the interferogram are selected. The complexity indicator composed of three complexity factors is used to guide the adaptive selection of the most suitable and effective filtering strategies for different areas. Then, the complexity scalar is calculated, which can guide the adaptive local fringe frequency estimation and adaptive parameters calculation in different filter methods. Finally, validations are performed on the simulated and real data. The performance comparison between the other three representative phase filtering method and the proposed method have validated the effectiveness and superiority of the proposed method.

An On-Site InSAR Terrain Imaging Method with Unmanned Aerial Vehicles

“…In [63], a median filter was cascaded with a mean filter based on stationary wavelet transform for phase filtering. The median filter exceled in preserving phase fringes, while the mean filter demonstrated superior noise reduction capabilities.…”