Road Network Extraction in VHR SAR Images of Urban and Suburban Areas by Means of Class-Aided Feature-Level Fusion

被引：39
|
作者：
Hedman, Karin [1 ]
Stilla, Uwe [2 ]
Lisini, Gianni [3 ]
Gamba, Paolo [3 ]
机构：
[1] Tech Univ Munich, Dept Astron & Phys Geodesy, D-80333 Munich, Germany
[2] Tech Univ Munich, Dept Photogrammetry & Remote Sensing, D-80333 Munich, Germany
[3] Univ Pavia, Dept Elect, I-27100 Pavia, Italy
来源：
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2010年 / 48卷 / 03期
关键词：
Markov random field (MRF); rapid mapping; road extraction; TerraSAR-X;
D O I：
10.1109/TGRS.2009.2025123
中图分类号：
P3 [地球物理学]; P59 [地球化学];
学科分类号：
0708 ; 070902 ;
摘要：
In this paper, we propose to combine two road extractors from very high resolution synthetic aperture radar scenes: one more successful in rural areas and one explicitly designed for urban areas. In order to get the best combination of both, a rapid mapping filter for discriminating rural and urban scenes is utilized. Finally, the results are fused on a feature level and connected by means of a network optimization. The approach is tested and evaluated on TerraSAR-X data containing complex urban areas and urban-rural fringe scenes.
引用
收藏
页码：1294 / 1296
页数：3
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