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An Efficient GPU-Based Implementation of the R-MSF-Algorithm for Remote Sensing Imagery

机译:基于GPU的R-MSF算法实现遥感图像的高效实现

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This paper presents an efficient real time implementation of the regularized matched spatial filter algorithm (R-MSF-Algorithm) for remote sensing (RS) imagery that employs the robust descriptive experiment design (DED) approach, using a graphics processing unit (GPU) as parallel architecture. The achieved performance is significantly greater than initial requirement of two image per second. The performance results are reported in terms of metrics as: number of operations, memory requirements, execution time, and speedup, which show the achieved improvements by the parallel version in comparison with the sequential version of the algorithm.
机译:本文介绍了用于遥感(RS)图像的正规化匹配空间滤波器算法(R-MSF算法)的有效实时实现,该图像采用鲁棒描述实验设计(DED)方法,使用图形处理单元(GPU)为并行架构。实现的性能明显大于每秒两张图像的初始要求。绩效结果在指标方面报告为:操作次数,内存要求,执行时间和加速,其显示与算法的顺序版本相比的并行版本的实现。

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