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Urban Road Extraction from High-Resolution Optical Satellite Images

机译:从高分辨率光学卫星图像中提取城市道路

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Road extraction research has always been an active research on automatic identification of remote sensing images. With the availability of high spatial resolution images from new generation commercial sensors, how to extract roads quickly, accurately and automatically has been a cutting-edge problem in remote sensing related fields. In this paper, we present a novel road extraction approach which uses a scale space segmentation and two measures of the shape index to filter all regions from the result of the segmentation. The approach makes full use of spectral and geometric properties of roads in the imagery, and proposes a new algorithm named "Road Segments joint Algorithm" to ensure the continuity of roads.
机译:道路提取研究一直是遥感图像自动识别的积极研究。借助新一代商用传感器提供的高空间分辨率图像,如何快速,准确,自动地提取道路已成为遥感相关领域的前沿问题。在本文中,我们提出了一种新颖的道路提取方法,该方法使用比例尺空间分割和两种形状指数度量从分割结果中过滤所有区域。该方法充分利用了图像中道路的光谱和几何特性,并提出了一种新的算法,称为“路段联合算法”,以确保道路的连续性。

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