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  • 标题:3D road extraction using a stereo pair of aerial images
  • 本地全文:下载
  • 作者:Aluir Dal Poz ; J. F. C. Silva ; Rodrigo Gallis
  • 期刊名称:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
  • 印刷版ISSN:2194-9042
  • 电子版ISSN:2194-9050
  • 出版年度:2010
  • 卷号:XXXVIII - Part 1
  • 出版社:Copernicus Publications
  • 摘要:Road extraction from aerial and satellite imagery is of fundamental importance in the context of spatial data capturing and updating for GIS (Geographic Information System) applications. This article proposes a semiautomatic methodology for 3D road extraction from digital images. The dynamic programming (DP) algorithm is used to carry out the optimisation process in the object-space, instead of doing it in the image-space such as the DP traditional methodologies. This means that road centrelines are directly traced in the object-space, implying that a mathematical relationship is necessary to connect road points in object- and image-space. This allows the integration of radiometric information from images into the associate energy function. Although the methodology can operate in different modes (mono-plotting or stereo-plotting), and with several image types, including multisensor images, this paper presents details of our stereo-based approach involving a stereo pair of aerial images. In order to initialise the extraction procedure, a few seed points are necessary to be supplied in the object-space to sparsely and coarsely describe the roads. We visually identify these points on the stereo images and project them onto the object-space. Each road is extracted separately by an iterative scheme based on the DP optimisation algorithm. Each iteration cycle is carried out by means of a polyline densification followed by a DP optimisation. The polyline densification is carried out by linearly interpolating middle points between every adjacent vertices of the current polyline. Preliminary results have shown that the proposed methodology works properly
  • 关键词:Dynamic Programming; Road Model; Feature Extraction; Road Extraction; Aerial Images
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