Point cloud top noise elimination method based on LiDAR

A noise and point cloud technology, applied in the field of laser point cloud classification, can solve the problems of clean noise removal and high noise density, and achieve the effect of high removal accuracy, high density, and reduced calculation time

Active Publication Date: 2018-03-20
广东电网有限责任公司机巡作业中心
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However, in a special climate environment, the generated noise density is high, clou

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  • Point cloud top noise elimination method based on LiDAR

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[0021] The present invention will be further described below in conjunction with the accompanying drawings. It should be noted that the accompanying drawings are only for illustrative purposes and should not be construed as limitations on this patent.

[0022] like figure 1 As shown, a LiDAR-based point cloud top noise removal method, the point cloud data is located in three-dimensional space coordinates, including the following steps:

[0023] S1: Establish a standard grid for the point cloud data on the XOY coordinate plane, set the grid side length parameter value, and obtain the height value H' of the lowest point in the Z-axis direction in each grid, that is, the Z of the lowest point coordinate value;

[0024] S2: After step S1, according to the spatial distribution characteristics of the point cloud data, obtain the height h of the continuous point-free cloud layer on the vertical height of each grid, and record the initial height value H of the continuous point-free c...

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Abstract

The invention relates to the technical field of laser point cloud classification, and more specifically, relates to a point cloud top noise elimination method based on LiDAR. A standard space grid isestablished for point cloud based on spatial clustering and spatial autocorrelation. The position of noise is determined according to the spatial distribution characteristic and interdependence of point cloud data. The grid units containing noise are determined according to the growth pattern of grid clustering. European clustering is carried out by using initially identified top noise as a seed point, in order to eliminate noise. The algorithm abandons one-by-one computation, and reduces the computation time. The problem that a good effect cannot be achieved in actual production due to poor general applicability, low efficiency or other reasons is solved. Cloud sheet-shaped, high-density and wide-range noise produced in a special climate environment can be eliminated with high accuracy.

Description

technical field [0001] The present invention relates to the technical field of laser point cloud classification, and more specifically, to a LiDAR-based point cloud top noise removal method. Background technique [0002] The LiDAR system acquires data from top to bottom in a blind scan manner, and the laser pulse may irradiate flying objects that are lower than the center of the pulse emission, or irradiate smooth surface objects that can generate multipath, resulting in a point cloud The data is noisy. At present, the denoising methods for point cloud data mainly include local plane fitting method, frequency domain method, three-dimensional finite element growth analysis method and elevation texture image classification method. In this case, the above algorithm can effectively remove noise. However, in a special climate environment, the noise point density is high, cloud-like and wide-ranging, and the above algorithm cannot be used to remove the noise point. Contents of...

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T5/002G06T2207/10028
Inventor 许志海陈剑光王丛杨鹏
Owner 广东电网有限责任公司机巡作业中心
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