| 一种基于分布式并行模型的海量机载LiDAR点云数据快速滤波方法 |
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| 引用本文： | 宇超群,邓勇,张静.一种基于分布式并行模型的海量机载LiDAR点云数据快速滤波方法[J].信息工程大学学报,2021,22(1):61-65. |
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| 作者姓名： | 宇超群 邓勇 张静 |
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| 作者单位： | 信息工程大学 |
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| 摘 要： | 机载Li DAR点云数据是遥感大数据的重要组成部分，基于单机的处理算法已经无法满足海量点云数据处理的要求。首先，针对现有单机多级移动曲面拟合滤波算法存在粗差和拟合曲面精度不高的问题，提出适合海量机载Li DAR点云数据滤波的多级多窗口移动曲面拟合滤波算法(WHMCFA);其次，设计并实现基于MapReduce的PWHMCFA并行滤波算法;最后，实验证明这种并行滤波算法在保证精度的前提下实现了海量机载Li DAR点云数据的快速滤波。
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| 关 键 词： | 海量点云 滤波 并行计算 MapReduce |
| 收稿时间： | 2020/9/13 0:00:00 |
| 修稿时间： | 2020/10/19 0:00:00 |
Fast Filtering of Massive Airborne LiDAR Point Cloud Data Based on MapReduce |
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| YU Chaoqun,DENG Yong,ZHANG Jing.Fast Filtering of Massive Airborne LiDAR Point Cloud Data Based on MapReduce[J].Journal of Information Engineering University,2021,22(1):61-65. |
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| Authors: | YU Chaoqun DENG Yong ZHANG Jing |
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| Affiliation: | Information Engineering University |
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| Abstract: | The airborne Li DAR point cloud data is an important part of remote sensing big data and its quantitative trend has become increasingly apparent. Processing algorithm based on single-machine cannot meet the requirements of point cloud processing any longer. To address such shortcomings as coarse deviation and low accuracy of fitting surface in the existing single machine hierarchical moving curved fitting algorithm,the improved WHMCFA algorithm is put forward first. Then the PWHMCFA parallel filtering algorithm based on MapReduce is designed and implemented. Experiments prove that fast filtering of massive airborne Li DAR point cloud data is realized without compromising the precision. |
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| Keywords: | massive point cloud filter parallel computing MapReduce |
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