基于多分辨率方向预测的LIDAR点云滤波方法

Filtering of LIDAR Points Clouds Based on Multi-resolution Directional Prediction

为了快速提取LIDAR点云中的地面点,生成高精度的DTM,提出了一种基于多分辨率方向预测的LIDAR点云滤波方法。该方法首先构建多种分辨率数据集,然后基于方向预测法以分辨率由低到高的顺序逐层进行数据集的平滑处理,最后以最高分辨率数据集的平滑结果为基准标记原始LIDAR点云。本方法通过分析反距离权重插值模型的不足,利用改进的模型进行裸露地面点的插值,得到高精度的DTM。实验表明,本文方法能有效地滤除地物,并保持原有的地形特征,算法效率高,具有一定的实用价值。

For extracting ground points from LIDAR points clouds quickly and generating high accurate DTMs effectively, a filtering method based on multi-resolution directional prediction is proposed. The method works by constructing multi-resolution datasets, smoothing datasets from low to high resolution based on directional prediction, and comparing the original LII）AR points clouds with the smoothed dataset to get bare ground points. The method improves the algorithm of ＂Inverse Distance to a Power＂ based on fixing its deficiencies in interpolating ground points. Highly accurate DTMs are interpolated by the proposed algorithm using bare ground points. It is confirmed that the algorithm is efficient in removing non-terrain objects and preserving terrain features, and holds promising potential for applications.