Progressive triangulated irregular network point cloud filtering method based on voxel

Abstract

The invention relates to a light detection and ranging (LiDAR) point cloud filtering method, in particular to a progressive triangulated irregular network point cloud filtering method based on voxel, which is applicable to airborne and ground-based radar point cloud data processing and belongs to the technical field of LiDAR point cloud data processing. The method comprises the following steps: loading LiDAR point cloud data; preprocessing the LiDAR point cloud data, and organizing and managing the point cloud data in a segmented way; determining a mathematical expression of LiDAR point cloud voxelization, and voxelizing point cloud; determining LiDAR point cloud multi-echo information, and retaining single echo and the last echo point in multiple echo; determining a mathematical expression of a LiDAR point cloud progressive triangulated irregular network, and filtering point cloud; and determining LiDAR point cloud multi-echo information, and retaining single echo and the last echo point in multiple echo. The method of the invention is applicable to complex terrain surfaces, is sensitive to detection of dense vegetation areas, steep slopes and irregular fracture zones, and can be used to generate a high-precision digital elevation model (DEM).

Description

technical field [0001] The present invention relates to a laser radar (LiDAR) point cloud filtering method, in particular to a voxel-based progressive irregular triangular network point cloud filter, which is suitable for airborne and ground-based radar point cloud data processing, and belongs to the laser radar point cloud data processing technology field. Background technique [0002] LiDAR (Light Detection And Ranging, LiDAR) is an active remote sensing technology that uses laser light emitted by the sensor to measure the distance between the sensor and the target. LiDAR data is an irregularly distributed point set in three-dimensional space, and the distribution form in three-dimensional space presents a discrete "point cloud". In order to generate a high-precision digital elevation model and subsequent object extraction and 3D reconstruction, the point cloud data must be filtered. The purpose of filtering is to separate ground points and non-ground points, and the esse...

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Problems solved by technology

[0007] Aiming at the low filtering effect of existing filtering methods under complex terrain, the present invention proposes a voxel-based progressive triangulation irregular filtering method, which has the advantage of being sensitive to dense forest-covered terrain, steep slopes, and irregular fracture factors of point clouds

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