统计费用网络流相位解缠并行处理

Parallel Computing Based on Statistical-Cost Network-Flow Algorithm for Phase Unwrapping

  • 摘要: 针对雷达干涉测量(InSAR)相位解缠中的单机计算资源不足和相对运算效率不高的问题,提出了数据并行处理策略。以统计费用网络流相位解缠为例,分析了该算法的数据划分方法,构建了并行运算实验系统,实现了统计费用网络流相位解缠并行处理,并从解缠效果、内存使用量和运算效率3个方面对实验结果进行了分析。

     

    Abstract: We introduce parallel computing to provide high performance computing and enough computing resources for massive remote sensing data processing. Based on Condor and SNAPHU(statistical-cost, network-flow algorithm for phase unwrapping), we build a parallel computing environment in cluster system for phase unwrapping. We analyze processing results in aspects of unwrapping accuracy, memory usage and computing efficiency, and conclude influencing factors in the three aspects. The experiment shows that parallel computing effectively solve the computing problem occurred in massive remote sensing data processing, such as memory shortage and inefficient computation.

     

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