Noise Filtering of High-Resolution Interferograms Over Vegetation and Urban Areas With a Refined Nonlocal Filter

Abstract

Interferometric synthetic aperture radar (SAR) filtering is a crucial processing step in topography reconstruction and deformation measurement. The high-resolution interferograms over vegetation or urban areas are heterogeneous, which will violate the local stationarity assumption and make it difficult to obtain a large number of independent and identically distributed samples for interferometric noise suppression. To overcome this problem, a refined nonlocal filter is proposed in this letter. Given coherence, topography phase, and expected SAR intensity of the pixel to be filtered, the similarity distance between the central pixel and other pixels in the searching window is measured by the normalized probability density function of the interferogram. Then, the outliers whose normalized probability density is smaller than the given threshold are removed from the filtering process. Finally, both simulated and real high-resolution interferograms are used to evaluate the effectiveness of the proposed method.