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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >An Adaptive Multifeature Method for Semiautomatic Road Extraction From High-Resolution Stereo Mapping Satellite Images
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An Adaptive Multifeature Method for Semiautomatic Road Extraction From High-Resolution Stereo Mapping Satellite Images

机译：高分辨率立体地图卫星图像半自动道路自适应多特征提取方法

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摘要

In this letter, an adaptive multifeature method for semiautomatic road extraction in high-resolution stereo mapping satellite images is proposed. First, the digital surface model (DSM) is generated from high-resolution stereo mapping satellite images by the semiglobal vertical line locus matching method. To combine the entropy feature and the spectral feature with the DSM, an adaptive method based on the image matching theory is introduced, which maintains a dynamic balance in the road extraction process and ensures the complementarity of each feature. Then, the geodesic road tracking method integrated with kernel density estimation and mean shift is used to extract roads from the feature fusion map. Experimental results have shown that the proposed method can extract roads both smoothly and correctly from high-resolution stereo mapping satellite images and especially performs better than other existing methods when there is an elevation difference between the road target and its neighborhood.
机译：在这封信中，提出了一种用于高分辨率立体地图卫星图像中半自动道路提取的自适应多特征方法。首先，通过半全局垂直线轨迹匹配方法从高分辨率立体映射卫星图像生成数字表面模型（DSM）。为了将熵特征和光谱特征与DSM相结合，提出了一种基于图像匹配理论的自适应方法，该方法在道路提取过程中保持动态平衡，并确保每个特征的互补性。然后，将结合核密度估计和均值漂移的测地线跟踪方法从特征融合图中提取出道路。实验结果表明，该方法能够从高分辨率立体地图卫星图像中平滑，正确地提取道路，特别是在道路目标与其邻域之间存在高程差异时，其性能优于其他现有方法。

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