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An object-oriented method for road damage detection from high resolution remote sensing images

机译:一种面向对象的高分辨率遥感影像道路损伤检测方法

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The precision of road damage detection in disaster area from high resolution remote sensing images is general low because the current methods are mainly based on pixels and can't combine with the already existing GIS information. This paper presents an object-oriented road damage detection method. First and foremost, Multi-scale segmentation technology is adopted to get image objects, and then the paper utilizes some typical feature parameters and combines with pre-disaster's GIS vector road to extract road information. Then the techniques of overlay analysis and violating objects removal are employed to extract the damaged road section. Remote sensing images for Wenchuan, China disaster area and Yushu, China disaster area are implemented as examples. The result indicates that this method can improve quickness and efficiency of road damage detection.
机译:由于目前的方法主要基于像素,并且不能与已经存在的GIS信息相结合,因此从高分辨率遥感影像中进行灾害区域道路损伤检测的精度普遍较低。本文提出了一种面向对象的道路损伤检测方法。首先,首先采用多尺度分割技术获取图像对象,然后利用一些典型的特征参数,并结合灾前的GIS矢量道路提取道路信息。然后采用覆盖分析和违章物体去除技术提取受损路段。以汶川,中国灾区和玉树,中国灾区的遥感图像为例。结果表明,该方法可以提高道路损伤检测的速度和效率。

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