CN113240808B

CN113240808B - Method for thinning LAS-format laser point cloud data

Info

Publication number: CN113240808B
Application number: CN202110327842.8A
Authority: CN
Inventors: 胡德承; 刘汉清; 赵锦江; 黄焕星; 林天; 余煜东
Original assignee: Guangdong Jiexin Surveying And Mapping Technology Co ltd; SHANTOU POLYTECHNICAL
Current assignee: Guangdong Jiexin Surveying And Mapping Technology Co ltd; SHANTOU POLYTECHNICAL
Priority date: 2021-03-26
Filing date: 2021-03-26
Publication date: 2023-01-03
Anticipated expiration: 2041-03-26
Also published as: CN113240808A

Abstract

The method for rarefying LAS-format laser point cloud data comprises the following steps: (1) Reading point data of an LAS point cloud data file, and simultaneously obtaining a point data distribution area range; (2) Constructing a regular triangular grid in a point data distribution area, wherein the side length (a) is a point distance (H) required by the density of the model, and the calculation formula is a = H; (3) Selecting the vertex of a regular triangle grid in a point data distribution area as a center, and taking tan 30-degree point distance as side length to construct a regular hexagon selection area, wherein the side length (A) calculation formula is as follows: a = tan30 ° × H; (4) Selecting the point data closest to the center of the regular hexagon in each selected area; (5) Deleting the data points except the data points selected in the step (4) to obtain data points after thinning; (6) And exporting all data points obtained by thinning to a data file to finish thinning. The method can realize the thinning of the high-density laser point cloud data under the condition of ensuring the three-dimensional ground modeling precision so as to improve the speed and the efficiency of the three-dimensional ground modeling.

Description

Method for thinning LAS format laser point cloud data

Technical Field

The invention relates to a method for rarefying LAS-format laser point cloud data, belonging to the field of information technology processing.

Background

The laser radar LIDAR (Light Detection And Ranging) is an active remote sensing technology which is rapidly developed in recent years, can quickly acquire three-dimensional coordinates of a ground target by integrating a Scanning Laser Ranging (SLR) technology, a Global Positioning System (GPS) technology And an Inertial Navigation System (INS) technology, and has wide application in the fields of high-precision Digital Elevation Model (DEM) acquisition, road And power line mapping, forest parameter measurement, urban modeling And the like. The LAS format is a standard exchange format for LIDAR data as specified by the LIDAR commission of the American Society of Photogrammetry and Remote Sensing (ASPRS). The LAS format file is a binary format file, well considers the characteristics of LIDAR data, has a reasonable structure, is convenient to expand, facilitates data exchange and sharing among different hardware manufacturers, software manufacturers and users, and powerfully promotes the development of LIDAR data processing software and popularization of LIDAR application.

The collected original laser point cloud data comprises ground points and non-ground points, and the point cloud density can be as high as more than 200 points per square meter. General laser point cloud data can be subjected to three-dimensional ground model construction only after data classification, thinning and the like of professional laser point cloud data processing software. However, the existing laser point cloud data processing software is expensive, can not directly output point data in a required format, requires a plurality of software such as Excel software and southern CASS software (based on an AutoCAD platform) to be matched with each other, and is complex to operate and easy to make mistakes. In addition, the laser point cloud data is obtained by measuring the ground target with high precision, so that the obtained data is huge, and if the data is directly converted into a three-dimensional model, the conversion difficulty is large and a modeling file is also huge. Under the condition that some models do not need to be finer, the problems of resource waste, low efficiency and the like exist. Therefore, under the premise of ensuring the three-dimensional ground modeling precision, the thinning of the laser point cloud data is very important.

Disclosure of Invention

In order to solve the defects, the invention provides a method for rarefying LAS-format laser point cloud data.

In order to achieve the purpose, the invention adopts the technical scheme that: the method for rarefying LAS-format laser point cloud data comprises the following steps:

(1) Reading point data of an LAS point cloud data file, namely X, Y, Z three-dimensional coordinates, and simultaneously obtaining a point data distribution area range;

(2) Constructing a regular triangle grid in a point data distribution area, wherein the side length a of the regular triangle grid is the point distance H required by the model density, and the calculation formula is a = H;

(3) Selecting the vertexes of a regular triangle grid in the point data distribution area, and constructing a regular hexagon selection area by taking the vertexes of the grid as the center and taking tan 30-degree point distance as the side length, wherein the side length A of the regular hexagon selection area is calculated by the following formula: a = tan30 ° × H;

(4) Selecting the data of the point closest to the center of the regular hexagon in each regular hexagon selection area;

(5) Deleting the data points other than the data points selected in the step (4) to obtain data points after thinning;

(6) And exporting all data points obtained by thinning to a data file to finish the thinning of the LAS-format laser point cloud data.

Preferably, the step (1) reads the size of the common header area of the LAS point cloud data file and the number of variable length records between the common header area and the point data to obtain the point data, i.e. the initial position of the X, Y, Z three-dimensional coordinate record.

Preferably, the point cloud data distribution area in the step (1) is covered by seamless adjacent selected regular hexagonal areas constructed by the regular triangular grid points in the step (3).

According to the invention, through a regular triangle grid point selection method, LAS format laser point cloud data is thinned according to the data requirement of actual three-dimensional ground modeling, the originally huge cloud point data is reduced according to the actual situation and then converted into a point data file required by the three-dimensional ground modeling, and therefore, under the condition of ensuring the three-dimensional ground modeling precision, the screening of the laser point cloud data is realized, and the speed and the efficiency of the three-dimensional ground modeling are improved. In addition, the method can uniformly divide the laser point cloud data into a plurality of selection areas for screening, so that the division of the selection areas is more uniform and compact, and reasonable differentiation of the data is realized.

Drawings

FIG. 1 is a schematic flow diagram of the present invention.

FIG. 2 is a schematic diagram of a regular triangle lattice point selection method of the present invention.

Detailed Description

The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. It is to be understood that the disclosed embodiments are merely exemplary of the invention, and are not intended to be exhaustive or exhaustive. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

As shown in fig. 1, the method for rarefying LAS-format laser point cloud data includes the following steps:

(1) Reading point data of an LAS point cloud data file, namely X, Y, Z three-dimensional coordinates, and meanwhile obtaining a point data distribution area range;

(2) Constructing a regular triangular grid in a point data distribution area, wherein the side length a of the regular triangular grid is the point distance H required by the model density, and the calculation formula is a = H;

(3) Selecting the vertexes of the regular triangle grids in the point data distribution area, and constructing a regular hexagon selection area by taking the vertexes of the grids as the center, wherein the side length A calculation formula is as follows: a = tan30 ° × H;

(4) Selecting the point data closest to the center of the regular hexagon in each regular hexagon selection area;

(5) Deleting the data points except the data points selected in the step (4) to obtain data points after thinning;

According to the invention, through a regular triangle grid point selection method, LAS format laser point cloud data is thinned according to the data requirement of actual three-dimensional ground modeling, the originally huge laser point cloud data is reduced according to the actual condition and then converted into a point data file required by the three-dimensional ground modeling, so that the screening of the laser point cloud data is realized under the condition of ensuring the three-dimensional ground modeling precision, and the speed and the efficiency of the three-dimensional ground modeling are improved.

In the step (1), the data recording position is positioned by reading the size of the public head area of the LAS point cloud data file and the variable length record number between the point data, so that data support is provided for reading the point data (X, Y, Z three-dimensional coordinates) of the LAS point cloud data file and obtaining the range of the point cloud data distribution area.

As shown in fig. 2, in the step (2), in the range of the point data distribution area, the point distance required by the model density is taken as the side length to construct a regular triangle mesh. In the figure, a thick solid line is a point data distribution area range, a first regular triangle is constructed by taking an upper left corner point of the point data distribution area range as a middle point of the right side of the regular triangle, and other regular triangles are connected to form a regular triangle grid under the condition that the point data distribution area is provided with a vertex. The adjacent regular triangle grids can ensure that the distances between the mesh points of the adjacent regular triangle grids are the same.

And (4) selecting the regular triangle lattice points in the point data distribution area, and constructing a regular hexagon selection area by taking the lattice points as centers and taking the tan 30-degree point distance as side length. As shown in fig. 2, a thick solid line is a point data distribution area range, regular triangle lattice points within the point data distribution area range are selected, and a regular hexagon selection area is constructed by taking the lattice points as a center and taking tan30 ° dot distance as side length. The regular hexagon selection area constructed by taking regular triangle grid points with the same adjacent point distance as centers can be completely uniform and seamlessly adjoined to the coverage point data distribution area range.

Because the LIDAR technology accurately scans ground targets to obtain data, the density of point cloud data is very high for the accuracy and authenticity of the data, namely, more point data are needed to realize accurate modeling. However, in some modeling environments where no particular precision is required, the huge data needs to be partially pruned. The method comprises the steps of constructing a screening selection area by adopting a regular triangle grid point selection method, namely constructing a regular triangle grid by taking one-time point distance required by model density as side length, constructing a regular hexagon selection area by taking a regular triangle grid point in a point cloud data distribution area as a center and taking tan 30-degree point distance as the side length, selecting point data closest to the center of a regular hexagon in each regular hexagon selection area, and deleting the point data outside the selection area to obtain data points which are uniformly distributed after thinning. The distance between the vertexes of the adjacent regular triangles is the same, and when the seamless adjacent regular hexagon selection area is constructed by taking the lattice point formed by the adjacent regular triangles as the center, the data can be uniformly divided into a plurality of selection areas for screening, so that the divided selection areas can be ensured to be more uniform and compact, and the reasonable differentiation of the data is realized. For example, a three-dimensional ground model needs to be constructed in a range of ten kilometers of a square circle, and the ratio of the model requirement to the real terrain is 1:1000. the method comprises the steps that the ground is scanned through a laser radar LIDAR technology to obtain three-dimensional laser point cloud data, a large amount of point data can be generated in the range of a point cloud data distribution area, the large amount of point data means that the accuracy of model building is high, the model building does not need to be accurate in the actual model building process, and most of the data points are redundant. Therefore, by the laser point cloud thinning method, a regular triangle grid is constructed by taking the point distance of 10 meters as the side length, and a regular hexagon selection area is constructed by taking the mesh point of the regular triangle grid in the point cloud data distribution area as the center and taking 10 multiplied tan30 degrees as the side length. Therefore, only one point data nearest to the center of the regular hexagon is selected in each selected area, and finally the point data reserved in all the selected areas is exported to obtain actually required modeling data, so that the data capacity is greatly reduced, and the modeling efficiency is improved.

Claims

The method for rarefying LAS format laser point cloud data is characterized by comprising the following steps:

(1) Reading point data of an LAS point cloud data file, namely X, Y, Z three-dimensional coordinates, and meanwhile obtaining a point data distribution area range;

(2) Constructing a regular triangular grid in a point data distribution area, wherein the side length a of the regular triangular grid is the point distance H required by the model density, and the calculation formula is a = H;

(3) Selecting the vertexes of a regular triangle grid in the point data distribution area, and constructing a regular hexagon selection area by taking the vertexes of the grid as the center and taking tan 30-degree point distance as the side length, wherein the side length A of the regular hexagon selection area is calculated by the following formula: a = tan30 ° × H; the regular hexagon selection area which is constructed by taking regular triangle grid points with the same adjacent point distance as the center can be completely uniform and seamlessly adjacent to the coverage point data distribution area range;

(4) Selecting the point data closest to the center of the regular hexagon in each regular hexagon selection area;

(5) Deleting the data points except the data points selected in the step (4) to obtain data points after thinning;

(6) And exporting all data points obtained by thinning to a data file to finish the thinning of the LAS-format laser point cloud data.
2. The method of claim 1, wherein the step (1) reads the common header size of the LAS point cloud data file and the variable length record number between the common header size and the point data to obtain the point data, i.e. the starting position of X, Y, Z three-dimensional coordinate record.