Towards 3D map generation from digital aerial images

被引:69
作者
Zebedin, Lukas [1 ]
Klaus, Andreas [1 ]
Gruber-Geymayer, Barbara [1 ]
Karner, Konrad [1 ]
机构
[1] VRVis Res Ctr Virtual Real & Visualizat, Graz, Austria
关键词
classification; aerial triangulation; dense image matching; information fusion; true ortho image;
D O I
10.1016/j.isprsjprs.2006.06.005
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
This paper describes the fusion of information extracted from multispectral digital aerial images for highly automatic 3D map generation. The proposed approach integrates spectral classification and 3D reconstruction techniques. The multispectral digital aerial images consist of a high resolution panchromatic channel as well as lower resolution RGB and near infrared (NIR) channels and form the basis for information extraction. Our land use classification is a 2-step, approach that uses RGB and NIR images for an initial classification and the panchromatic images as well as a digital surface model (DSM) for a refined classification. The DSM is generated from the high resolution panchromatic images of a specific photo mission. Based on the aerial triangulation using area and feature-based points of interest the algorithms are able to generate a dense DSM by a dense image matching procedure. Afterwards a true ortho image for classification, panchromatic or color input images can be computed. In a last step specific layers for buildings and vegetation are generated and the classification is updated. (C) 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:413 / 427
页数:15
相关论文
共 18 条
[1]  
[Anonymous], P EUR
[2]  
[Anonymous], 2005, LIBSVM LIB SUPPORT V
[3]  
[Anonymous], INT ARCH PHOTOGRAMME
[4]  
Bauer J., 2004, INT ARCH PHOTOGRA B3, V35, P1119
[5]  
Bolter R., 2001, BUILDINGS SAR DETECT
[6]   High-quality texture reconstruction from multiple views [J].
Bornik, A ;
Karner, K ;
Bauer, J ;
Leberl, F ;
Mayer, H .
JOURNAL OF VISUALIZATION AND COMPUTER ANIMATION, 2001, 12 (05) :263-276
[7]  
Collins R.T, 1995, P C COMP VIS PATT RE, P358
[8]  
Hsu C.W, 2008, PRACTICAL GUIDE SUPP
[9]   An assessment of support vector machines for land cover classification [J].
Huang, C ;
Davis, LS ;
Townshend, JRG .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2002, 23 (04) :725-749
[10]  
Lowe D.G., 1999, P IEEE INT C COMP VI, P1150, DOI DOI 10.1109/ICCV.1999.790410