Intelligent filtering method for airborne laser point cloud data

A technology of laser point cloud data and point cloud data, which is applied in the field of remote sensing surveying and mapping, can solve problems affecting the intelligent processing of LiDAR point cloud data, achieve the effects of improving processing efficiency and filtering accuracy, avoiding interference, and improving the degree of intelligence

Active Publication Date: 2013-02-13
GUANGZHOU JIANTONG SURVEYING MAPPING & GEOINFORMATION TECH
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AI Technical Summary

Problems solved by technology

Noise has a great impact on LiDAR point cloud filtering, but the existing denoising algorithms often cannot handle this type of noise well, and the existing filtering algorithms basically process the noise separately before filtering, which also greatly affects the LiDAR point cloud. Intelligent data processing process

Method used

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  • Intelligent filtering method for airborne laser point cloud data
  • Intelligent filtering method for airborne laser point cloud data
  • Intelligent filtering method for airborne laser point cloud data

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specific Embodiment

[0072] A specific embodiment of the present invention is as follows:

[0073] S100. Read the laser point cloud data, and then use the grid index to organize the points contained in the laser point cloud data to generate a dense point cloud grid and a sparse point cloud grid. Here, all points are divided and organized according to their coordinate rules, respectively Generate a dense point cloud grid of 1m×1m and a sparse point cloud grid of 4m×4m;

[0074] S101, using the elevation value of the lowest point in each grid in the sparse point cloud grid of 4m×4m as the gray value, and then generating the first elevation image map I h ;

[0075] S102, respectively calculate and generate the first elevation image map I h X-direction gradient map I x and Y direction gradient map I y , the specific calculation formula is as follows:

[0076]

[0077]

[0078] Wherein, W and H are respectively the width and height of the first elevation image map, and i and j are all natura...

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Abstract

The invention discloses an intelligent filtering method for airborne laser point cloud data. The method comprises the following steps of: reading laser point cloud data to ensure that points contained in laser point cloud data of a grid index organization generate one dense point cloud grid and a sparse point cloud grid; classifying the sparse point cloud grid to obtain an urban area and a mountain area; dividing the urban area and the maintain area by using different windows respectively to extract the local lowest point of each window; extracting to obtain an initial ground point by using the local lowest point as a seed point by area growing-based intelligent division; and establishing a triangulated irregular network (TIN) model according to the initial ground point so as to progressively encrypting the TIN model and iteratively extract ground points. In the processing process, manual intervention is not required, the interference of noise points can be effectively avoided, and the processing efficiency and filtering accuracy of the airborne laser-point cloud data can be improved. The excellent intelligent filtering method for the airborne laser-point cloud data can be widely applied to surveying and mapping industry.

Description

technical field [0001] The invention relates to the field of remote sensing surveying and mapping, in particular to a filtering method for airborne laser point cloud data. Background technique [0002] LiDAR (Lidar) scanning system integrates GNSS (Global Navigation Satellite System), INS (Inertial Navigation System) and laser scanning system. It can directly measure the three-dimensional coordinates of space points, and can obtain digital surface models efficiently and quickly. The current airborne LiDAR technology can obtain data with a horizontal resolution of 10-20cm, and the number of points measured in an air strip often exceeds tens of millions. How to process LiDAR data quickly and efficiently becomes a problem worthy of research. Although the current commercial LiDAR systems often come with many software toolkits for processing LiDAR data, in practical applications, a lot of manual intervention is still required, such as filter parameter setting and manual editing ...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 胡翔云叶立志
Owner GUANGZHOU JIANTONG SURVEYING MAPPING & GEOINFORMATION TECH
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