Research on a GB-SAR interferogram filtering method for open-pit mines based on eight-neighbourhood outlier discrimination

Ground-based synthetic aperture radar (GB-SAR) interferograms contain a large amount of phase noise. The existing methods lose effective deformation information to varying degrees upon filtering, which seriously reduces the monitoring accuracy of GB-SAR. In this paper, a GB-SAR interferogram filtering method for open-pit mines is studied. First, permanent scatterer points (PSPs) are extracted through coarse filtering, and the distribution of the noise phase is analysed. Then, an improved Grubbs outlier discrimination criterion is introduced considering the uncertainty of the PSP distribution. A method based on the eight-neighbourhood outlier discrimination (EOD) criterion is proposed to identify noise points. High-coherence points (HCPs) are used to reconstruct the phase of the noise points to filter the GB-SAR interferogram. Finally, the filtering effect is quantitatively evaluated using the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The superiority of the proposed filtering method in the image displacement region is verified based on simulated and real deformation data. The results show that the proposed method can accurately filter out the phase noise of interferograms and improve the accuracy of GB-SAR for slope monitoring.