Phase Unwrapping Algorithm for Large Interferogram in Shared Memory Environment

In order to solve the unwrapping problem of low efficiency for large interferogram, we propose a new phase unwrapping algorithm in shared memory environment, which is designed based on quality-guided and minimum discontinuity optimization strategies. The three processes, phase quality map computing, high and low quality area's partition and low quality area's optimization, are parallelized in shared memory environment. In order to fully use the multi-core computing ability, a dynamic allocation method for computing task is designed for the optimization process of low quality areas. Unwrapping tests performed on simulated and InSAR interferogram show that the proposed algorithm improves the high quality of unwrapped result and greatly optimizes the efficiency.