Semi-Automated Road Detection From High Resolution Satellite Images by Directional Morphological Enhancement and Segmentation Techniques
Semi-Automated Road Detection From High Resolution Satellite Images by Directional Morphological Enhancement and Segmentation Techniques
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DOI：
10.1109/jstars.2012.2199085
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发表时间：
2012-10-01
影响因子：
5.5
通讯作者：
Samal, A.
中科院分区：
文献类型：
--
作者：
Chaudhuri, D.;Kushwaha, N. K.;Samal, A.
从高分辨率卫星图像中提取道路、河流、建筑物等地图目标是许多民用和军事应用中的重要任务。我们提出了一种半自动的道路检测方法，实现了高精度和高效率。该方法利用道路段的属性来开发定制的算子以精确地导出道路段。定制的算子包括方向形态增强、方向分割和细化。我们已经系统地评估了各种图像从IKONOS，QuickBird，CARTOSAT-2A卫星的算法，并仔细比较它与文献中提出的技术。实验结果表明，该算法具有较高的精度和效率.
Extraction of map objects such roads, rivers and buildings from high resolution satellite imagery is an important task in many civilian and military applications. We present a semi-automatic approach for road detection that achieves high accuracy and efficiency. This method exploits the properties of road segments to develop customized operators to accurately derive the road segments. The customized operators include directional morphological enhancement, directional segmentation and thinning. We have systematically evaluated the algorithm on a variety of images from IKONOS, QuickBird, CARTOSAT-2A satellites and carefully compared it with the techniques presented in literature. The results demonstrate that the algorithm proposed is both accurate and efficient.