融合LiDAR点云与正射影像的建筑物图割优化提取方法

杜守基; 邹峥嵘; 张云生; 何雪; 王竞雪

doi:10.11947/j.AGCS.2018.20160534

测绘学报 >

2018 , Vol. 47 >Issue 4: 519 - 527

DOI: https://doi.org/10.11947/j.AGCS.2018.20160534

摄影测量学与遥感

融合LiDAR点云与正射影像的建筑物图割优化提取方法

杜守基 ,
邹峥嵘 ,
张云生 ,
何雪 ,
王竞雪

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1. 中南大学地球科学与信息物理学院, 湖南长沙 410083;
2. 辽宁工程技术大学测绘与地理科学学院, 辽宁阜新 123000

杜守基(1990-),男,工程硕士,研究方向为点云建筑物提取与三维变化检测。E-mail:dsjcug@163.com

收稿日期: 2016-10-25

修回日期: 2017-07-12

网络出版日期: 2018-05-02

基金资助

国家重点研发计划（2016YFC0803108）；国家自然科学基金（41201472）；卫星测绘技术与应用国家测绘地理信息局重点实验室开放基金（KLSMTA-201505）

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A Building Extraction Method via Graph Cuts Algorithm by Fusion of LiDAR Point Cloud and Orthoimage

DU Shouji ,
ZOU Zhengrong ,
ZHANG Yunsheng ,
HE Xue ,
WANG Jingxue

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1. School of Geosciences and Info-Physics, Central South University, Changsha 410083, China;
2. School of Geomatics, Liaoning Technical University, Fuxin 123000, China

Received date: 2016-10-25

Revised date: 2017-07-12

Online published: 2018-05-02

Supported by

The National Key Research and Development Program of China(No. 2016YFC0803108);The National Natural Science Foundation of China (No. 41201472);The Open Research Fund of Key Laboratory of Satellite Mapping Technology and Application,National Administration of Surveying,Mapping and Geoinformation (No. KLSMTA-201505)

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摘要

提出一种基于图割算法的建筑物LiDAR点云与正射影像融合提取方法。首先，利用LiDAR点云计算3个几何特征：平整度、法向量分布和高程纹理一致性。同时利用航空正射影像计算颜色特征——归一化植被指数（NDVI）。然后将两类特征联合构建能量函数数据项，综合数字表面模型（DSM）和NDVI构建平滑项，采用图割算法优化得到初始的建筑物区域。最后利用初始建筑物边缘一定范围内的正射影像颜色信息，采用前后景分割的思想进一步优化建筑物边缘。应用ISPRS Vaihingen测试数据进行试验，结果表明本文方法具有较高的建筑物提取精度。

关键词： 建筑物提取; 激光点云; 正射影像; 图割算法; 建筑物边缘优化

本文引用格式

杜守基 , 邹峥嵘 , 张云生 , 何雪 , 王竞雪 . 融合LiDAR点云与正射影像的建筑物图割优化提取方法[J]. 测绘学报, 2018 , 47(4) : 519 -527 . DOI: 10.11947/j.AGCS.2018.20160534

Abstract

An automatic building extraction method based on graph cuts algorithm fusing LiDAR point cloud and orthoimage is proposed.Firstly,three geometric features are computed from LiDAR points including flatness,distribution of normal vector and GLCM (grey level co-occurrence matrix) homogeneity of normalized height.NDVI is simultaneously calculated from orthoimage.After that,both kinds of features are combined to construct the data term of energy function,then DSM and NDVI is combined to construct smooth term.Thereafter,graph cuts algorithm is applied to obtain the initial building extraction results.Finally,foreground and background segmentation method is employed to optimize the building boundary based on the orthoimage color information in certain range of the initially detected building boundary.ISPRS Vaihingen dataset is used to evaluate the proposed method.The results reveal that the proposed method can obtain high accuracy of the detection building area.

Key words： building extraction; LiDAR point cloud; orthoimage; graph cuts algorithm; building boundary optimization

参考文献

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