实时机载LiDAR数据多面体建筑提取方法

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"从机载LiDAR数据中动态提取多面体建筑物" 本文提出了一种实时处理机载光检测和测距（LiDAR）数据的方法，用于动态提取多面体建筑物。LiDAR系统通过发射激光脉冲并测量其回波时间来获取地表的三维信息，这对于建筑物的精确建模至关重要。该方法首先利用网格化技术，将激光足迹的平面位置和高程数据转换成数据序列，使得点云数据更加有序。接着，应用离散平稳小波变换(DSWT)来分析序列中的高程变化。小波变换是一种数学工具，可以用来分析数据在不同尺度上的变化，这对于识别建筑物等具有显著高度差异的特征非常有效。序列的细节小波系数包含了高频信息，这些信息对应于建筑物的边缘和突变，因此可以从这些系数中识别出建筑物的存在。为了进一步提高提取精度，文章还引入了对相邻扫描线数据的梯度分析。通过对扫描线方向上建筑物屋顶的几何平面内的网格点进行梯度计算和校正，可以修正由于点云噪声或不精确性导致的误差。这种方法有助于保持建筑物边界的平滑性和一致性，从而提升提取结果的准确性。该方法的独特之处在于其“动态”特性，能够在数据采集的同时进行处理，即“on-the-fly”，这使得数据处理更加高效，尤其是在处理大量LiDAR数据时。通过这种方式，可以在激光点沿扫描线移动的过程中实时提取建筑物，极大地提高了处理速度和实时响应能力。实验证明，这种新方法在实际的机载LiDAR数据集上表现出了良好的性能。通过与传统方法的对比和验证，它能够准确地提取扫描区域内的多面体建筑物，对于城市环境中的建筑物检测和三维重建具有重要的应用价值。此方法不仅适用于建筑物的自动检测，也为城市规划、地理信息系统(GIS)更新以及灾害风险评估等领域提供了强有力的技术支持。

1946 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 11, NO. 11, NOVEMBER 2014

On-the-Fly Extraction of Polyhedral Buildings

From Airborne LiDAR Data

Lijun Xu, Senior Member, IEEE, Deming Kong, and Xiaolu Li, Member, IEEE

Abstract—This letter presents an on-the-ﬂy method for extract-

ing polyhedral buildings from airborne light detection and ranging

(LiDAR) data. By using the gridding method, the planimetric po-

sition and elevation of laser footprints (normally treated as points)

in the obtained scan line are mapped into a data sequence. Then,

discrete stationary wavelet transform is applied to analyze the

elevation variation in the sequence. Buildings in the scan line can

be obtained from the detail wavelet coefﬁcients of the sequence.

Moreover, to improve precision of the extraction, the gradients

of grid points in the geometric planes of building roofs along the

direction of the scan line are calculated and remedied by using

the corresponding gradients acquired from the adjacent scan lines.

With the proposed on-the-ﬂy method, polyhedral buildings in the

scan area can be accurately extracted from laser points along

the scan lines during the scanning process. The new method is

validated by using a set of real airborne LiDAR data.

Index Terms—Building extraction, light detection and ranging

(LiDAR), on-the-ﬂy data processing, remote sensing.

I. INTRODUCTION

URRENTLY, airborne light detection and ranging

(LiDAR) has been widely used in high-precision topog-

raphy, terrain investigation, and Earth observation. Compared

with traditional aerial photogrammetry, airborne LiDAR is less

affected by natural factors, such as weather and illumination

conditions, because the elevation values of ground and objects

on the ground can be directly obtained using the laser beam

emitted by a LiDAR instrument [1].

In the geographic information system, buildings are an indis-

pensable component. Due to their palpable artiﬁcial features,

buildings are often used as key objects in urban planning,

disaster prevention and control, national defense, and many

other applications of remote sensing. Consequently, the re-

search on rapid and high-precision extraction of buildings from

airborne LiDAR data has drawn wide attention [2]. Many

effective building extraction methods have been proposed, such

as the methods based on point cloud segmentation [3], range

Manuscript received September 29, 2013; revised January 6, 2014 and

March 18, 2014; accepted March 21, 2014. Date of publication April 22, 2014;

date of current version May 22, 2014. This work was supported in part by

the National Basic Research Program of China (973 Program) under Grant

2009CB72400106 and in part by the National Natural Science Foundation of

China under Grant 61121003, Grant 61201316, and Grant 61225006.

L. Xu is with the Ministry of Education’s Key Laboratory of Precsion

Opto-Mechatronics Technology, School of Instrument Science and Opto-

Electronic Engineering, Beihang University, Beijing 100191, China (e-mail:

lijunxu@buaa.edu.cn).

D. Kong and X. Li are with the State Key Laboratory of Inertial Science and

Technology, School of Instrument Science and Opto-Electronic Engineering,

Beihang University, Beijing 100191, China.

Color versions of one or more of the ﬁgures in this paper are available online

at http://ieeexplore.ieee.org.

Digital Object Identiﬁer 10.1109/LGRS.2014.2314458

image processing [4], polygon generation [5], and 2-D wavelet

transform [6]. A common assumption in these studies is that

buildings have a polyhedral form [7], i.e., buildings only have

planar roofs. By using the aforementioned methods, polyhedral

buildings can be detected and extracted from airborne LiDAR

data. However, in real applications, there is a common short-

coming: all the aforementioned methods are more suitable for

processing LiDAR data in the schistose form (i.e., point cloud

or range image generated from the point cloud) than for directly

processing LiDAR data in each raw scan line obtained in the

scanning process. Since the point cloud cannot be obtained

until the whole ﬂight over the target area is ﬁnished, building

extraction by using the aforementioned methods is generally

considered as a post-treatment process instead of an on-the-ﬂy

process.

Over time, the line-scan frequency of airborne LiDAR in-

struments has increased signiﬁcantly, up to 200 Hz for Riegl

LMS-Q680i, for instance. Nearly real-time extraction of build-

ings can be achieved if rapid processing of scan lines during

the LiDAR scanning process is realized. Methods have been

proposed. According to Axelsson [8], break points located in

the elevation waveforms of scan lines, i.e., the grid points

whose second derivatives of elevation values are nonzero, are

selected to extract the boundaries of the buildings. We found

in real applications that the elevation differences between the

leafy crowns of tall trees and the ground are quite similar with

the differences between roofs and the ground. Therefore, if

considering only the break points in the scan lines, buildings

cannot be accurately differentiated from tall trees.

The objective of this letter is to develop an on-the-ﬂy method

to accurately extract polyhedral buildings from airborne LiDAR

data. Discrete stationary wavelet transform [9] is introduced

to detect buildings from the LiDAR data along the scan lines.

From the obtained detail wavelet coefﬁcients, both the break

points and the gradient information of grid points along the

direction of the scan line can be acquired. By comparing the

gradient information of grid points in the scan line with the cor-

responding information of grid points in the adjacent scan lines,

buildings in the scan line can be accurately differentiated from

trees. Consequently, polyhedral buildings in the scan area can

be extracted nearly in real time during the scanning process of

airborne LiDAR.

II. M

ETHODOLOGY

A. Elevation Sequence Generation

In most applications, the airborne LiDAR instruments are

operated in parallel line-scan mode. Ideally, the obtained laser

IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.

See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

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