一种融合图像分割信息的激光雷达数据滤波新算法

Zhenghui Xu, Ling-xiang Liu, Xiaodong Liu
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引用次数: 1

摘要

传统的LiDAR点云滤波和分类算法多基于高程信息,单一数据源难以区分裸地点和非地点。本文采用融合图像信息进行滤波。通过图像分割,提取每个分割对象的形状和光谱信息,然后将这些向量空间对象与点云进行匹配,并基于拓扑关系建立决策树进行滤波。为了测试所提算法的性能,采用了具有较厚建筑物和道路的测试区域,可以获得较好的滤波效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new filtering algorithm for lidar data fused with image segmentation information
The traditional LiDAR Point Cloud filtering and classification algorithms are mostly based on the elevation information, which are difficult to distinguish bare-ground and non-ground point with this single data source. In this article, fused image information such is used in the filtering process. Through the image segmentation, each segmentation object are extracted with the shape and spectral information, then these vector space objects and point cloud are matched and the decision tree is set up based on topology relationship for filtering. In order to test the performance of the proposed algorithm, test area with thick buildings and roads were applied, which could achieve a better filtering effect.
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