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Automatic roads extraction from high-resolution remote sensing images based on SOM

机译:基于SOM的高分辨率遥感影像道路自动提取

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An efficient method based on SOM neural network is proposed for extracting road networks from the high resolution remote sensing image. Firstly, the road region segmented used improved methods. Then the original image is divided into some grids, and the original weighs of neurons. The road center nodes in the grids were won the SOM algorithm which is inspired from a specialized variation of SOM neural network. Finally, using “Four-Direction Tracking” approach, the road centerlines were tracked automatically. The experiment results show that this method is capable of rapidly and accurately extracting main road networks in addition to its good robustness to noise.
机译:提出了一种基于SOM神经网络的有效方法,用于从高分辨率遥感图像中提取道路网络。首先,道路区域分割采用改进的方法。然后将原始图像划分为一些网格,并原始称量神经元。网格中的道路中心节点赢得了SOM算法,该算法的灵感来自SOM神经网络的一种特殊变化。最后,使用“四方向跟踪”方法,自动跟踪道路中心线。实验结果表明,该方法除具有良好的抗噪声能力外,还能够快速,准确地提取主要道路网络。

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