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Geometry-based SAR curvilinear feature selection for damage detection

机译:基于几何的SAR曲线特征选择用于损伤检测

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摘要

Bright curvilinear features in Synthetic Aperture Radar (SAR) images arising from the geometry of urban structures have been successfully used for estimating urban earthquake damage, using single pre- and post-event high resolution amplitude SAR images. In this paper, further automation of the process of selecting candidate curvilinear features for change detection is proposed, based on a model selection using priors derived from idealised building geometry. The technique is demonstrated using COSMO-SkyMed data covering the 2010 Port-au-Prince earthquake.
机译:通过使用单个事前和事后高分辨率振幅SAR图像,合成孔径雷达(SAR)图像中由城市结构几何引起的明亮曲线特征已成功用于估算城市地震破坏。在本文中,基于使用从理想化的建筑几何体派生的先验的模型选择,提出了用于选择候选曲线特征以进行变化检测的过程的进一步自动化。使用涵盖2010年太子港地震的COSMO-SkyMed数据演示了该技术。

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