Comparisons of Speckle Noise Filtering Methods on Interferometric Synthetic Aperture Radar Images

Abstract

Speckle noise in interferometric synthetic aperture radar (InSAR) phase images seriously degrades the quality of interferogram, disenables interferogram to reflect accurate phase characteristics of the target and increases the difficulty in extracting DEM information of the target area. Therefore, reducing speckle noise by interferogram filtering is a significant step in InSAR processing. First, a noise-included interferometric SAR phase image is simulated based on a terrain model and geometrical parameters of InSAR system. The phase image can be characterized by multilook phase distribution. Then, three interferogram filtering algorithm are explored to remove speckle noise: Goldstain filter, rotating kernel transformation and Lee filter. Proper implementation of three methods is given. Based on experimental results, performances of three different methods are compared. Two aspects need to be comprehensively considered in noise reduction process: the required accuracy in practical application and the processing duration. And also secondtime or multiple combined noise reduction is highly recommended.

SAR Interferogram Filtering of Shearlet Domain Based on Interferometric Phase Statistics

“…Since the real and imaginary parts of the phase are periodic characteristics, the phase is wrapped from (−π, π). Therefore, the filtering should be performed on the real and imaginary parts separately to maintain the phase jumps [30].…”

“…We first get the real and imaginary parts of the phase, and then process them by the shearlet transform respectively. The continuous shearlet transform is defined as below [30].…”

“…The standard deviation of a given coherence and multi-look number can be calculated by numerical integration [30]. Correspondingly, the phase standard deviation map can be calculated pixel by pixel with the coherence map and multi-look factor through numerical integration.…”

A Novel and Optimized Sine–Cosine Transform Wavelet Threshold Denoising Method Based on the sym4 Basis Function and Adaptive Threshold Related to Noise Intensity

“…In order to improve the accuracy of phase unwrapping, speckle noise needs to be filtered [14]. Several methods have been proposed to filter the speckle noise of the wrapped phase pattern, which mainly focuses on the spatial and transform domains.…”