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Optimized parallelization of non-local means filter for image noise reduction of InSAR image

机译:非局部均值滤波器的优化并行化以降低InSAR图像的图像噪声

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Non-local means filter is widely used for image noise reduction. Although the sequential implementation for this algorithm has been successfully applied to large scale InSAR problems, few parallel versions of the non-local InSAR filters have addressed well algorithm characteristics such as an unpredictable workload balance, a strong data dependency. These challenges engender many interesting design issues including domain decomposition, data access, management and workload balancing. This paper presents a sophisticated and improved parallel scheme for the iterative non-local Interferometric Synthetic Aperture Radar (InSAR) filters. The proposed algorithm gives a better speedup and high efficiency. Results for numerical simulations and performance measurements were obtained on SuperMUC.
机译:非局部均值滤波器被广泛用于图像降噪。尽管此算法的顺序实现已成功应用于大规模InSAR问题,但很少有并行版本的非本地InSAR过滤器很好地解决了算法特征,如不可预测的工作负载平衡,强烈的数据依赖性。这些挑战带来了许多有趣的设计问题,包括域分解,数据访问,管理和工作负载平衡。本文为迭代非局部干涉式合成孔径雷达(InSAR)滤波器提出了一种完善的改进并行方案。所提出的算法具有更好的加速性能和较高的效率。在SuperMUC上获得了数值模拟和性能测量的结果。

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