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Road extraction from SAR Images by using a graphical sketch of road

机译:使用道路图形从SAR图像中提取道路

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摘要

The subject of this communication is the detection of roads on SAR images starting from a user-drawn graphical sketch. This sketch is considered as a road model, and the main contribution of this communication is to incorporate this model in a yet-existing blind road detection method to improve the quality and reliability of the detection. The method combines both local and global criteria for road extraction. It consists of mainly two parts. First local information is extracted by applying a low-level operator, based on a line detector taking into account the statistical properties of speckle in SAR images. In the second step, road detection is performed by selecting the best road in a graph composed of all the detected segments and all possible connections between them. To demonstrate the contribution of the use of a model in the road detection, we first introduce an "exact" model of the road (extracted for instance from a road map), in order to validate the method. Then the method is applied with an un-precise model (both in form and position). The obtained results from different SAR images are presented and evaluated with objective criteria.
机译:该通信的主题是从用户绘制的图形草图开始在SAR图像上检测道路。该草图被视为道路模型,此通信的主要作用是将该模型合并到尚不存在的盲道检测方法中,以提高检测的质量和可靠性。该方法结合了本地和全局道路提取标准。它主要包括两个部分。通过基于线检测器并考虑SAR图像中斑点的统计特性,通过应用低级运算符来提取第一局部信息。在第二步中,通过在由所有检测到的路段以及它们之间的所有可能连接组成的图形中选择最佳道路来执行道路检测。为了证明在道路检测中使用模型的贡献,我们首先引入道路的“精确”模型(例如从道路地图中提取),以验证该方法。然后,将该方法应用于不精确的模型(形式和位置)。呈现并展示了从不同SAR图像获得的结果,并以客观标准进行了评估。

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