A registration method of airborne and vehicle LiDAR point clouds considering the characteristics of eaves
A point cloud registration and feature point technology, applied in computer parts, image analysis, image enhancement, etc., can solve the problems of inapplicable eaves area, few airborne and vehicle LiDAR features with the same name, etc., and achieve short cycle and low cost. , fast effect
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Publication Date
- 2022-03-25
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Abstract
Description
technical field
[0001] The invention belongs to the technical field of mobile measurement, and in particular relates to an airborne and vehicle-mounted LiDAR point cloud registration method in consideration of eaves features. Background technique
[0002] The LiDAR (Light Detection and Ranging, LiDAR) system integrates sensors such as laser scanners, global satellite navigation systems, and inertial navigation systems, and can quickly obtain three-dimensional high-precision laser point clouds. The LiDAR system can obtain terrain three-dimensional data information with high efficiency, high precision, automation and directness through high-speed laser scanning measurement. Compared with traditional measurement methods, LiDAR measurement is basically not limited by light and weather conditions, and has the advantages of short cycle, fast speed, low cost, and high efficiency, which fully meets the timeliness requirements of 3D terrain modeling and updating, and has a relatively...
Examples
Embodiment Construction
[0059] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:
[0060] In order to achieve the above object, the present invention adopts the following technical solutions:
[0061] A point cloud registration method for airborne and vehicle-mounted LiDAR that takes into account the characteristics of the eaves. The process is as follows: figure 1 shown, including the following steps:
[0062] Step 1: Denoise and filter the airborne LiDAR (Airborne Laser Scanning, ALS) and vehicle-borne LiDAR (Vehicle-borne Laser Scanning, VLS) point cloud data, and extract building point clouds and feature corners from ground object points;
[0063] Denoise and filter the airborne and vehicle-mounted LiDAR point cloud data, and use existing technology to extract building point clouds and feature corners;
[0064] Step 2: Establish a local neighborhood similarity measurement model to realize fast automatic matching of pseud...