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A Method for Automatical Extraction of Typical Disaster-bearing Targets from LiDAR Point Cloud in Coastal Zone

机译:一种自动提取沿海地区激光脉云典型灾害目标的方法

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This paper presents a method based on georeferenced feature image to automatically extract typical disaster-bearing targets from coastal LiDAR data. Firstly, the noise and the water surface of LiDAR point cloud are removed by using the elevation histogram. Secondly, by analyzing the spatial distribution of point cloud, the georeferenced feature image of point cloud is generated. Finally, the image processing method and the corresponding relationship between the three-dimensional point cloud and the two-dimensional feature image are used to realize the automatic extraction of the targets. In this paper, the LiDAR cloud data of Haidian Island acquired by ALS70, is used as experimental data to verify the feasibility and practicability of the proposed method.
机译:本文介绍了一种基于地理学特征图像的方法,从沿海LIDAR数据自动提取典型的灾害目标。首先,通过使用仰角直方图除去LIDAR点云的噪声和水面。其次,通过分析点云的空间分布,生成了点云的地理学特征图像。最后,使用图像处理方法和三维点云和二维特征图像之间的相应关系来实现目标的自动提取。在本文中,ALS70获得的海淀岛的LIDAR云数据被用作实验数据,以验证所提出的方法的可行性和实用性。

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