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

机译:基于类辅助特征水平融合的城市及郊区VHR SAR图像路网提取

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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.
机译:在本文中,我们建议结合高分辨率高分辨率合成孔径雷达场景中的两种道路提取器:一种在农村地区取得成功,另一种针对城市地区明确设计。为了获得两者的最佳组合,使用了用于区分乡村和城市场景的快速映射过滤器。最后,将结果融合在功能级别上,并通过网络优化进行连接。该方法在包含复杂市区和城乡边缘场景的TerraSAR-X数据上进行了测试和评估。

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