Parallel Quality-Guided Phase Unwrapping Algorithm in Shared Memory Environment

We proposed a parallel quality-guided phase unwrapping algorithm in shared memory environment. The intrinsic relationship between the neighboring phase points about quality value computing is analyzed firstly, and then the row and column arrays are used to store the intermediate results in order to eliminate the repeated computation of gradient. The computing task is allocated by row, which can simplify the computing of row and column gradient mean values. Finally, the allocation of computing task is realized using OpenMP instructions, and the quality map is computed in parallel. The inherent parallelism of quality guided process is also analyzed in-depth, but subject to the repetitive thread startup and exit overhead, it is difficult to reflect the advantage of speed. Unwrapping tests performed on InSAR and InSAS interferogram show that the proposed method greatly improves the efficiency of phase unwrapping, and provides a foundation for improving the solution precision under real-time conditions.