A robust unwrapping method for local noise phase

Phase unwrapping algorithm is difficult to apply in INSAR image for the local high-density noise phase attributed to significant blocky noise. To achieve its application in such case, the pixels of noise phase are first detected, and are set to 0 with the automatic mask technique. For the phase that has a blocky noise region, the iteration algorithm of phase filling based on Least-Squares is developed in this study by calculating the unwrapping coefficient k to rebuild the true phase. The algorithm is promoted by MPIPU's ability to fill in the missing phase; it can also significantly suppress the error transfer attributed to iteration filling in the non-mask phase. Some experiments are performed on simulated data. As revealed from the results, the proposed method exhibits robust performance of phase unwrapping on local noise phase.