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首页> 外文期刊>International journal of image and data fusion >Urban road classification in geometrically integrated high-resolution RGB aerial and laser-derived images using the artificial neural network classification method
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Urban road classification in geometrically integrated high-resolution RGB aerial and laser-derived images using the artificial neural network classification method

机译：使用人工神经网络分类方法在几何集成高分辨率RGB航拍和激光衍生图像中进行城市道路分类

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The problem of automated urban road network extraction is extremely complex because roads in urban scenes strongly interact with other objects. This problem can be simplified if road regions are first isolated using a classification procedure. The isolated road regions can be posteriorly used in tasks of refinement and reconstruction of the road network. This article addresses only the problem of road regions' detection using Artificial Neural Network as classification method. However, in urban areas, the use of spectral data alone commonly leads to the confusion of the road class with other classes in RGB images, such as building roofs and concrete, because these objects may present similar spectral characteristics. To overcome this problem, it is proposed the integration of a high-resolution RGB aerial image with laser-derived images. The classification results showed that the integration of the geometric (height) and radiometric (laser pulse intensity) laser data significantly improved the classification accuracy, also contributing for the better detection of road pixel. The laser intensity data help to overcome the effects of road obstructions caused by shadows and trees. On the other hand, the laser height data help to separate the aboveground objects from those on the ground level.
机译：城市道路网络自动提取的问题非常复杂，因为城市场景中的道路会与其他物体强烈相互作用。如果首先使用分类程序隔离道路区域，则可以简化此问题。隔离的道路区域可以在道路网络的优化和重建任务中使用。本文仅解决使用人工神经网络作为分类方法的道路区域检测问题。但是，在城市地区，仅使用光谱数据通常会导致道路类别与RGB图像中的其他类别（如建筑物屋顶和混凝土）混淆，因为这些对象可能具有相似的光谱特征。为了克服这个问题，提出了将高分辨率的RGB航空图像与激光衍生的图像进行集成。分类结果表明，几何（高度）和辐射（激光脉冲强度）激光数据的集成显着提高了分类精度，也有助于更好地检测道路像素。激光强度数据有助于克服阴影和树木造成的道路阻塞的影响。另一方面，激光高度数据有助于将地面上的物体与地面上的物体分开。

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