机载激光雷达点云数据处理理论与应用研究606(7)

Abstract

With the increasing local market demands of LIDAR technology and equipment,

the post processing software of LIDAR point cloud is always used corresponding

commercial software. The surveying and mapping products of these softwares are

incomplete in according with the corresponding criterion of China. Not only on the

respect of drawing efficiency but also on the respect of drawing ideas, the processing

of LIDAR point cloud is very different from the conventional measuring data.

Therefore, combining with commercial point cloud processing software and domestic

surveying and mapping criterions and developing a point cloud data processing

software that is suitable for domestic surveying and mapping products is a totally

necessary and urgent.

The researched processing software, PCEdit, is based on the rich information of

point cloud and Digital Orthophoto Map (DOM), used AutoCAD as development

platform and objectARX as development tool in virtue of visual C++8.0. Combining

point cloud with DOM, we can get lots of surveying and mapping products, such as

Digital Line Graphs (DLG), Digital Raster Graphic (DRG), Digital surface model

(DSM) and so on. This paper is mainly focuses on the key points as follows:

The input and display of point cloud is the first step of data processing.

Considering the low efficiency of general point cloud input and edit, this paper

derives a custom point entity using Object DBX. In this way, each point cloud file can

be imported into database as one entity along with one handle, which makes the

browsing and roaming of this file more convenient.

In filtering, interpolation and compression of point cloud, it is very frequent to

accessing some points, such as searching, insertion and deleting. In order to

improving the accessing efficiency, the idea of dynamic window is put forward. By

pulling the vertex of the minimum rectangle (cuboid) of poind cloud, we can find the

interesting area to edit, which can avoid accessing the whole point cloud data but

focus only on the certain point cloud data in rectangle (cuboid). Therefore, a high

efficiency in editing and displaying the point cloud can be acquired.

Since different densities of point cloud are needed in different objects, the idea of

sampling, erase and interpolating point cloud based on closed polygon and strip area

is necessary, which accelerate the speed of producing surveying and mapping.

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