A novel two-step noise reduction approach for interferometric phase images

Abstract

Abstract Interferometric phase filtering is a key step in InSAR data processing. However, when utilizing interferometric phase filtering methods, it is difficult to preserve useful phase information while eliminating as many residuals as possible. This paper proposes a novel two-step noise reduction approach for interferometric phase images. This method uses the amended matrix pencil model to extract the main phase component of the interferometric phase in combination with a simple and effective adaptive window determination method for the first time. Then, fast non-local means filtering is used to extract an accurate residual phase component. Finally, the principal phase component extracted in the first step is summed with the residual component from the second step to obtain the final result. Several common interferometric phase filtering methods are compared using two sets of simulated data and one set of real TanDEM-X InSAR data. The results show that the proposed method can not only preserve useful phase information but also effectively remove residuals. In addition, the proposed method boasts a superior filtering efficiency.