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Runways detection based on scattering similarity and structural characteristics

机译：基于散射相似性和结构特征的跑道检测

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摘要

In this paper, a new algorithm of runways detection based on classification is proposed for PolSAR image, in which scattering similarity and structural characteristics of airport runways are used as target feature for classification. Firstly, training sample templates are built by initial terrain classification with scattering similarity. Then, Bayesian classification is used to classify the whole image. Finally, morphology filtering and the runways structural features such as parallels, topologic property are used to detect real runways. Multi-look fully polarimetric SAR data acquired by U.S. UAVSAR systems is used to verify the proposed algorithm. Experimental results show that the novel method can detect runways effectively and has a low false alarm rate. Besides, the detected runways keep an intact structure and clear outlines.
机译：本文提出了一种基于分类的新跑道检测算法，用于POLSAR图像，其中机场跑道的散射相似性和结构特征用作分类的目标特征。首先，训练样本模板由具有散射相似性的初始地形分类构建。然后，贝叶斯分类用于对整个图像进行分类。最后，使用形态过滤和跑道结构特征，如公平，拓扑属性，用于检测真正的跑道。 U.S.UAVSAR系统获取的多外观完全偏振SAR数据用于验证所提出的算法。实验结果表明，新型方法可以有效地检测跑道，具有低误报率。此外，检测到的跑道保持完整的结构和清晰的轮廓。

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