An Efficient and Adaptive Approach for Noise Filtering of SAR Interferometric Phase Images

Abstract

This letter presents a new efficient phase filtering algorithm for synthetic aperture radar interferometric phase images. Based on the additive noise model, we assume that the phase without noise is composed of principal phase components and residual phase components. A new two-step adaptive filtering algorithm based on this assumption is then developed. First, the principal phase components are adaptively estimated using the frequency spectrum with an adaptive bound and removed from the original noisy phase; thus, a residual noisy phase is obtained. Second, spatial filtering is carried out on this residual noisy phase image using four directional masks. The filter equals three other common filters when three different special bound parameters are set accordingly. This algorithm is effective, particularly for the interferometric phase images with tightly packed fringes or low coherence. Numerical results obtained with synthetic and real data show a significant improvement with respect to other conventional filtering algorithms in some situations of the proposed approach.