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Reconstruction of Residential Buildings by Detail Analysis of multi-aspect InSAR Data

机译:通过多方面InSAR数据的详细分析重建住宅

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State-of-the-art SAR sensors suggest utilizing InSAR-Data for the analysis of dense urban areas. The appearance of buildings in SAR or InSAR data is characterized by the effects of the inherent oblique scene illumination, such as layover, occlusion by radar shadow and multipath signal propagation. Therefore, especially in dense built-up areas reconstruction quality can be improved by a combined analysis of multi-aspect data.rnThe presented approach focuses on reconstruction of buildings in residential districts supported by knowledge based analysis considering the mentioned SAR-specific effects. The algorithm of building extraction starts with the segmentation of primitives, such as lines and edges, followed by the assembly of building hypotheses based on typical building features like linearity and right-angularity. The subsequent post-processing of building hypotheses contains the analysis of InSAR phases to improve footprint or to detect roof-type of buildings. The results are presented by using optical data and a high resolution LIDAR surface model as ground truth data.
机译:最新的SAR传感器建议利用InSAR数据来分析密集的市区。 SAR或InSAR数据中建筑物的外观以固有的倾斜场景照明的影响为特征,例如上空,雷达阴影遮挡和多径信号传播。因此,特别是在密集的建筑区域,可以通过多方面数据的组合分析来提高重建质量。rn本文提出的方法着重于居民区建筑物的重建,并在考虑到SAR特有效果的基础上进行基于知识的分析。建筑物提取的算法始于图元的分割,例如线和边,然后基于典型的建筑物特征(如线性和直角)组装建筑物假设。建筑物假设的后续后处理包含InSAR阶段的分析,以改善占地面积或检测建筑物的屋顶类型。通过使用光学数据和高分辨率LIDAR表面模型作为地面真实数据来显示结果。

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