Threshold-irrelative point cloud filtering method and device for airborne laser radar

Abstract

The invention relates to the field of digital cartography technology, in particular to a threshold-irrelative point cloud filtering method and device for an airborne laser radar. The technical scheme comprises the following steps: 1) segmenting point cloud data and constructing triangulated irregular network (TIN) of the initial ground; 2) generating point cloud-ground altitude difference data; and 3) conducting filter processing based on the statistics of point cloud-ground altitude difference. The threshold-irrelative point cloud filtering method and device has the beneficial effects that by utilizing the integral statistical characteristics, the method and device is not necessary to adopt thresholds directly related to geometric characteristics of the point cloud data such as the altitude difference and slope to realize airborne Lidar point cloud data filtering process, so that the manual intervention of the whole filtering data processing course is reduced, and the working efficiency of the whole airborne Lidar point cloud data processing is improved.

Description

technical field [0001] The present invention relates to the technical field of digital mapping, in particular to a threshold-independent airborne lidar point cloud filtering method and device, which is suitable for automatic processing of airborne lidar point clouds and separates ground and non-ground point clouds. A statistical filtering method and device. Background technique [0002] In recent years, airborne lidar technology has become an important means to obtain high-precision digital elevation model (DEM). The point cloud data obtained by airborne lidar often includes ground point cloud data and non-ground point cloud data. In order to construct a digital elevation model (DEM), it is usually necessary to separate the ground point cloud data from the non-ground point cloud data in Lidar, that is, to filter the non-ground point cloud data from the original Lidar point cloud data through a filtering method. The Lidar point cloud data filtering method needs to artif...

AI Technical Summary

Problems solved by technology

Using this threshold-related method often has a potential problem: for the Lidar point cloud data filtering process of different terrains, the adjustment of the manual experience threshold setting will lead to a sharp increase in workload

[0006] Judging from the prior art methods for Lidar point cloud data filtering described above, these methods often need to manually set some thresholds based on experience in the actual filtering process, and setting these thresholds often requires a lot of practice to accumulate experience. And select the threshold based on this experience, which actually brings a sharp increase in the workload of Lidar point cloud data filtering and low efficiency in the processing process

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