Abstract
Phase noise reduction is one of the key steps for synthetic aperture radar interferometry data processing. In this article, a novel phase filtering method is proposed. The main innovation and contribution of this research is to 1) incorporate local fringe frequency (LFF) compensation technique into the nonlocal phase filtering method to include more independent and identically distributed samples for filtering; 2) modify the nonlocal phase filter from three aspects: 1) executing nonlocal filtering in the complex domain of the residual phase to avoid gray jumps in phase, 2) adaptively calculating the smoothing parameter based on the LFF and the coherence coefficient, and 3) using the integral image in similarity calculation to improve the efficiency; 3) perform Goldstein filter in high coherence areas to reduce the computation expense. Experiments based on both simulated and real data have shown that the proposed method has achieved a better performance in terms of both noise reduction and edge preservation than some existing phase filtering methods.
Highlights
S YNTHETIC aperture radar interferometry (InSAR) is an important technique for obtaining high-precision digital elevation model (DEM) and surface deformation of a wide area [1]
To reduce the influence of fringe on the matching of similar patches, we propose to compensate for the local fringe before nonlocal filtering and present the improved nonlocal filtering for the residual phase
To improve the similarity matching ability of traditional NL-InSAR in areas with dense fringe, a new nonlocal noise suppression method has been proposed, which consists of three main steps
Summary
S YNTHETIC aperture radar interferometry (InSAR) is an important technique for obtaining high-precision digital elevation model (DEM) and surface deformation of a wide area [1]. The existence of thermal noise, decorrelation, undersampling, and other factors will lead to various phase noise. The residual points caused by phase noise will reduce the success rate of phase unwrapping, and further affect the estimation accuracy of elevation and deformation. How to effectively suppress the phase noise before phase unwrapping has been a focus of study in InSAR processing [2]. Phase filtering is the basic method to reduce phase noise, and its performance mainly depends on the number of pixels. Manuscript received April 3, 2021; revised July 7, 2021 and September 6, 2021; accepted September 11, 2021.
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