共享内存环境下的并行质量引导相位解缠

提出了一种共享内存环境下的并行质量引导相位解缠算法。首先，分析了相邻相位点质量值计算的内在关系，采用行、列数组保存中间结果消除梯度的重复计算；然后，按行进行计算任务分配，简化相邻窗口内的行、列均值计算；最后，通过OpenMP指令实现计算任务分配，完成质量图的并行计算。对于质量引导过程内在的并行性进行了分析，但受限于重复的线程启动和退出时间开销，难以体现速度优势。对合成孔径雷达干涉（synthetic aperture radar interferometry，InSAR）和干涉合成孔径声纳（interferometric synthetic aperture sonar，INSAS）干涉相位图进行解缠实验，结果表明，所提方法提高了相位解缠效率，为在实时条件下进一步提高相位解缠精度奠定了基础。

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.