Abstract

ABSTRACTThis article proposes a new filter for interferometric synthetic aperture radar (InSAR) phase denoising. Traditional phase filters generally face two major challenges: to preserve texture details while reducing noise and to perform well in less time. The local linear model-based guided filter and Stein’s unbiased risk estimate (SURE)-based filter, in contrast, have a high quality of edge-preserving performance and high efficiency owing to the feature of SURE formula and simplicity. Nevertheless, as these filters are designed for general digital images, they are not suitable for periodic and high-noise-level interferometric phase images. In this article, we modified the original filters by considering the coherence coefficient and features of the interferometric phase image, creating a new patch-based filter adapted to areas characterized by different coherences. Moreover, after obtaining the solution of a patch, considering the geometric closeness and the phasic similarity, we used a bilateral filter combining the pixels in the patch to obtain the estimate. Experimental results based on the simulated and real data confirmed the effectiveness of the proposed algorithm.

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