共享内存环境下的大块干涉相位图解缠算法

Phase Unwrapping Algorithm for Large Interferogram in Shared Memory Environment

  • 摘要: 针对大块干涉相位图解缠效率低的问题,提出了一种共享内存环境下的大块干涉相位图解缠方法。利用质量引导和最小不连续优化策略设计了复合相位解缠算法,并在共享内存环境下对算法中的质量图计算、高低质量区域分割和低质量区域优化3个步骤进行了并行化。为充分利用多核计算资源,针对低质量区域的并行优化,设计了动态计算任务分配方法。对仿真和干涉合成孔径雷达相位图的解缠试验结果表明,所提算法在提高相位解缠精度的同时,也极大地优化了相位解缠效率。

     

    Abstract: 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.

     

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