Double-element multi-primitive hierarchical filtering method for airborne laser radar point cloud

Abstract

The invention discloses a double-primitive multi-resolution hierarchical filtering method for airborne laser radar point cloud. The filtering method comprises the following steps: firstly, segmentingan original point cloud into a point cloud block set (block primitive) and a scatter point set (point primitive) based on surface smoothness; then judging the attribute (ground point or non-ground point) of each point through an improved multi-resolution hierarchical filtering method, finally dividing the point cloud block into a ground block and a non-ground block according to the attribute of each point, and dividing the scatter points into ground points and non-ground points. According to the method, a point cloud partitioning algorithm is fused, and then when the attribute of each point inthe original point cloud is judged, M estimation is introduced to carry out plane fitting so as to replace an interpolation ground reference plane in an existing filtering method, so that the classification precision of the point cloud is improved; and finally, respectively the types of the point cloud blocks and the scattered points are judged by utilizing the attribute of each point, so that more ground points can be reserved, and the filtering precision of the original point cloud is improved.

Description

technical field [0001] The invention relates to a dual-element multi-resolution hierarchical filtering method for airborne laser radar point clouds. Background technique [0002] With the development of LiDAR (Light Detection And Ranging, LiDAR for short) technology, airborne LiDAR has gradually become a mainstream tool for collecting ground point information. Compared with traditional photogrammetry methods, airborne lidar can penetrate vegetation and can accurately obtain topographic information in forested areas. However, the original point cloud data obtained by airborne lidar contains various non-ground information such as buildings, bridges, vehicles and vegetation, so these non-ground points need to be filtered out before building a digital elevation model (Digital Elevation Model, referred to as DEM). . Currently commonly used filtering methods can be divided into interpolation-based, slope-based, segmentation-based and morphology-based filtering according to the p...

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Problems solved by technology

However, since this filtering method judges whether the point is a ground point through the distance from the point to the ground reference surface generated by TPS interpolation, this judgment method may introduce some non-ground points in dense vegetation areas, reducing the filtering of the original point cloud. Accuracy, it can be seen that the filtering accuracy of the existing MHC filtering method needs to be further improved in areas with terrain fractures and complex scenes

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