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Stroke Width Transform for Linear Structure Detection: Application to River and Road Extraction from High-Resolution Satellite Images

机译:用于线性结构检测的笔划宽度变换:在高分辨率卫星图像的河流和道路提取中的应用

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The evaluation of lines of communication status in normal times or during crises is a very important task for many applications, such as disaster management and road network maintenance. However, due to their large geographic extent, the inspection of the these structures surfaces using traditional techniques such as laser scanning poses a very challenging problem. In this context, satellite images are pertinent because of their ability to cover a large part of the surface of communication lines, while offering a high level of detail, which makes it possible to discriminate objects forming these linear structures. In this paper, a novel approach for extracting linear structures from high-resolution optical and radar satellite images is presented. The proposed technique is based on the Stroke Width Transform (SWT), which allows parallel edges extraction from the input image. This transform has been successfully applied in the literature to extract characters from complex scenes based on their parallel edges. An adaptation of this transform to solve the problem of rivers extraction from Synthetic Aperture Radar (SAR) images and roads identification from optical images is described in this paper, and the results obtained show the efficiency of our approach.
机译:对于正常应用或危机期间的通信线路评估,对于许多应用程序(例如灾难管理和道路网络维护)而言是一项非常重要的任务。然而,由于它们的地理范围大,使用诸如激光扫描的传统技术对这些结构表面的检查提出了非常具有挑战性的问题。在这种情况下,卫星图像之所以具有相关性,是因为它们具有覆盖通信线路大部分表面的能力,同时又提供了高水平的细节,从而可以区分形成这些线性结构的物体。本文提出了一种从高分辨率光学和雷达卫星图像中提取线性结构的新方法。所提出的技术基于笔划宽度变换(SWT),它允许从输入图像中提取平行边缘。这种转换已在文献中成功应用,可以根据复杂场景的平行边缘从复杂场景中提取字符。本文描述了这种变换的适应性,以解决从合成孔径雷达(SAR)图像中提取河流和从光学图像中识别道路的问题,并且所获得的结果证明了我们方法的有效性。

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