Phase unwrapping algorithm for images with local high-density noise

Abstract

Due to undersampling and the local phase with local high-density noise, it is still difficult to develop a robust phase unwrapping algorithm. In order to resolve this issue, here, we propose what we believe to be a novel multiple path-following phase unwrapping (MPIPU) algorithm based on the shearing interference principle to recover the undersampling phase (non-noise). By calculating the unwrapping coefficient k, the phase iteration filling algorithm based on least-squares is developed for the high-density noise region in order to reconstruct the three-dimensional surface topography of interferometric synthetic aperture radar (InSAR) data. The proposed algorithm takes advantage of the MPIPU’s ability to fill in the missing phase with fitting data and can successfully suppress the error transfer caused by the blocky noise phase iteration process. Several experiments are conducted using both simulated and actual InSAR image data. The experimental findings show that the proposed method can achieve robust phase unwrapping performance on a phase of local high-density noise.