SAR Tomography with Improved Non-Local Means Filtering Based on Adaptive Window

Abstract

In order to mitigate speckle noise in synthetic aperture radar (SAR) images and enhance the accuracy of SAR tomography, non-local means (NL-means) filtering has been proven to be an effective method for improving the quality of SAR interferograms. Apart from considerations like noise type and the definition of similarity, the size and shape of filtering windows are critical factors influencing the efficacy of NL-means filtering, yet there has been limited research on this aspect. This paper introduces an enhanced NL-means filtering method based on adaptive windows, allowing for the automatic adjustment of filtering window size according to the amplitude information of the SAR interferogram. Simultaneously, a directional window is incorporated to align SAR interferograms, achieving the dual objective of preserving filtering standards and retaining detailed information. Experimental results on interferogram filtering and tomography, based on TerraSAR-X data, demonstrate that the proposed method effectively reduces phase noise while maintaining texture accuracy, thereby improving tomography quality.

Keywords

NL-means filter / adaptive window / SAR interferogram filtering / SAR tomography