Biquaternion Fourier Domain Filter for InSAR Noise Suppression by Enhancing Polarimetric-Interferometric Fringe Patterns

The Goldstein-Werner (GW) filter is one of the most widely used methods to suppress noise in interferometric synthetic aperture radar (InSAR) data. However, the insufficient filtering performance in highly noisy areas remains unsolved. In this article, we propose a biquaternion Fourier domain (BQFD) filter to improve the filtering performance even in highly noisy areas. This method represents polarimetric synthetic aperture radar interferometry (PolInSAR) data in a biquaternion form to process interferometric fringes of different polarimetric channels as a single signal. By using the biquaternion Fourier transform (BQFT), the fringes can be effectively separated from noise due to the high correlation of the fringes and the low correlation of noise between the polarimetric channels. In the experiments, we find that the BQFD filter produces more accurate digital elevation models (DEMs) than those produced with the GW filter. We also find that the accuracy of DEMs can be further improved by choosing an axis of the BQFT adaptively in each filtering window.