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- 2018
CPU和GPU协同的多光谱影像快速波段配准方法
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Abstract:
随着遥感影像数据量的飞速增长，传统的串行波段配准方法已无法满足大数据多光谱影像的实时配准需求。针对该问题，提出了一种CPU和GPU协同的多光谱影像快速波段配准方法。首先进行计算量和并行度分析，将同名点匹配和微分纠正映射至GPU执行，仿射变换系数拟合仍驻留在CPU执行。其次通过核函数任务映射和基本设置，使算法步骤在GPU上可执行，并设计了3种性能优化方法（访存优化、指令优化、传输计算堆叠），进一步提高了波段配准的执行效率。在NVIDIA Tesla M2050 GPU和Intel Xeon E5650 CPU组成的实验平台上，对遥感26号卫星多光谱影像的实验表明，使用该方法加速后的波段配准执行时间仅为3.25 s，与传统串行方法相比，加速比达到了32.32倍，可以满足大数据多光谱影像的近实时配准需求
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