基于外周弹性约束的矿坑密集点云滤波方法

Filtering Method of the Pit Dense Point Cloud Based on Peripheral Elastic Constraint

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摘要针对露天矿坑地形复杂、坑壁陡峭、灌丛密布,传统DEM采集与处理方法难以获取精细DEM的问题,借鉴布料模拟滤波思路,提出了一种面向倾斜摄影测量密集点云的矿坑外周弹性约束滤波算法。该方法在滤波网格优化的基础上,将下凹地形按高差微分为若干皮筋,通过模拟皮筋形变过程,得到与地面相近的皮筋网,从而分离出地面点,生成DEM。以徐州市某废弃矿坑为例,对提出的滤波算法进行了试验验证。与常用的滤波算法相比,试验结果准确率提高了10.15%,在地形起伏较大区域表现良好,滤波准确率为81.73%。随机选取的地面点与插值生成的高程之间拟合优度为0.830,均方根误差为0.048。试验结果表明:所提方法数据获取成本低、效率高,能够有效提取出矿坑地面点,可为矿区提供高精度的矿坑DEM数据。 In view of the characteristics of complex terrain,steep pit wall and dense thickets of the pit,it is difficult to obtain a fine DEM by traditional DEM acquisition and processing methods.Referring to the idea of cloth simulation filtering,an elastic constraint filtering algorithm for a pit dense point cloud of oblique photogrammetry is proposed in this paper.Based on the optimization of filtering grid,the concave terrain is differentiated into several elastics according to the height difference.By simulating the deformation process of elastics,the elastic meshes close to the ground is obtained,so as to separate the ground points and generate the DEM.Taking an abandoned mine in Xuzhou as an example,the proposed filtering algorithm is verified by experiments.Compared with the commonly used filtering algorithm,the accuracy of the experimental results is improved by 10.15%.It performs well in the area with large topographic relief,and the filtering accuracy is 81.73%.The goodness of fit be-tween the randomly selected ground points and the interpolated elevation is 0.830,and the root mean square error is 0.048.The experimental results show that the method proposed in this paper has low data acquisition cost and high efficiency,and can effectively extract the pit ground points,so as to provide the high-precision pit DEM data for the mining area.

作者熊何喜孙久运闫志刚张新耐 XIONG Hexi;SUN Jiuyun;YAN Zhigang;ZHANG Xinnai(School of Environment and Spatial Informatics,China University of Mining and Technology,Xuzhou 221116,China)

机构地区中国矿业大学环境与测绘学院

出处《金属矿山》 CAS 北大核心 2023年第9期127-133,共7页 Metal Mine

基金国家自然科学基金面上项目(编号:41971370) 2021年江苏省产学研合作项目(编号:BY2021449)。

关键词露天矿布料模拟密集点云弹性约束网格优化 DEM open-pit mine cloth simulation filtering dense point cloud elastic constraint grid optimization DEM

分类号 TD176 [矿业工程—矿山地质测量]