Acta Geodaetica et Cartographica Sinica >

2016 , Vol. 45 >Issue 10: 1231 - 1240

DOI: https://doi.org/10.11947/j.AGCS.2016.20160158

Fusion of Pixel-based and Object-based Features for Road Centerline Extraction from High-resolution Satellite Imagery

  • CAO Yungang ,
  • WANG Zhipan ,
  • SHEN Li ,
  • XIAO Xue ,
  • YANG Lei
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  • 1. State-province Joint Engineering Laboratory of Spatial Information Technology of High-speed Railway Safety, Southwest Jiaotong University, Chengdu 611756, China;
    2. Faculty of Geosciences and Environmental Engineering Southwest Jiaotong University, Chengdu 611756, China;
    3. Sichuan Province Second Geographic Information Engineering Institute of Surveying and Mapping, Chengdu 610100, China

Received date: 2016-04-07

  Revised date: 2016-06-16

  Online published: 2016-11-08

Supported by

The National Basic Research Program of China(973 Program) (No.2012CB719901);The National Natural Science Foundation of China (Nos. 41201434;41401374);The Key Laboratory of Digital Mapping and Land Information Application of National Administration of Surveying, Mapping and Geoinformation(No.DM2016SC06);Geographical Condition Monitoring Engineering Technology Research Center of Sichuan Province((No.GC201516))

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Abstract

A novel approach for road centerline extraction from high spatial resolution satellite imagery is proposed by fusing both pixel-based and object-based features. Firstly, texture and shape features are extracted at the pixel level, and spectral features are extracted at the object level based on multi-scale image segmentation maps. Then, extracted multiple features are utilized in the fusion framework of Dempster-Shafer evidence theory to roughly identify the road network regions. Finally, an automatic noise removing algorithm combined with the tensor voting strategy is presented to accurately extract the road centerline. Experimental results using high-resolution satellite imageries with different scenes and spatial resolutions showed that the proposed approach compared favorably with the traditional methods, particularly in the aspect of eliminating the salt noise and conglutination phenomenon.

Key words： high resolution remote sensing; multiple feature fusion; road extraction; pixel-based; object-based

Cite this article

CAO Yungang , WANG Zhipan , SHEN Li , XIAO Xue , YANG Lei . Fusion of Pixel-based and Object-based Features for Road Centerline Extraction from High-resolution Satellite Imagery[J]. Acta Geodaetica et Cartographica Sinica, 2016 , 45(10) : 1231 -1240 . DOI: 10.11947/j.AGCS.2016.20160158

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