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首页> 外文期刊>Geoscience and Remote Sensing, IEEE Transactions on >Robust Reconstruction of Building Facades for Large Areas Using Spaceborne TomoSAR Point Clouds
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Robust Reconstruction of Building Facades for Large Areas Using Spaceborne TomoSAR Point Clouds

机译：使用星载TomoSAR点云对大面积建筑立面进行稳健的重建

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摘要

With data provided by modern meter-resolution synthetic aperture radar (SAR) sensors and advanced multipass interferometric techniques such as tomographic SAR inversion (TomoSAR), it is now possible to reconstruct the shape and monitor the undergoing motion of urban infrastructures on the scale of centimeters or even millimeters from space in very high level of details. The retrieval of rich information allows us to take a step further toward generation of 4-D (or even higher dimensional) dynamic city models, i.e., city models that can incorporate temporal (motion) behavior along with the 3-D information. Motivated by these opportunities, the authors proposed an approach that first attempts to reconstruct facades from this class of data. The approach works well for small areas containing only a couple of buildings. However, towards automatic reconstruction for the whole city area, a more robust and fully automatic approach is needed. In this paper, we present a complete extended approach for automatic (parametric) reconstruction of building facades from 4-D TomoSAR point cloud data and put particular focus on robust reconstruction of large areas. The proposed approach is illustrated and validated by examples using TomoSAR point clouds generated from a stack of TerraSAR-X high-resolution spotlight images from ascending orbit covering an approximately 2- $hbox{km}^{2}$ high-rise area in the city of Las Vegas.
机译：利用现代的米分辨率合成孔径雷达（SAR）传感器和先进的多通道干涉测量技术（例如层析SAR反演（TomoSAR））提供的数据，现在可以重建形状并监视厘米级城市基础设施的运动甚至离太空只有几毫米的距离。丰富信息的检索使我们朝着生成4-D（甚至更高维）动态城市模型（即可以将时间（运动）行为与3-D信息结合在一起的城市模型）迈进一步。受这些机会的激励，作者提出了一种方法，该方法首先尝试从此类数据中重建立面。该方法适用于仅包含几栋建筑物的小区域。但是，要实现整个城市区域的自动重建，就需要一种更强大且完全自动化的方法。在本文中，我们提出了一种从4-D TomoSAR点云数据对建筑物立面进行自动（参数）重建的完整扩展方法，并将重点放在大型的鲁棒重建上。地区。通过使用TomoSAR点云举例说明并验证了所提出的方法，该点云是从一系列TerraSAR-X高分辨率聚光图像生成的，这些图像来自上升轨道，覆盖约2个 $ hbox {km} ^ {2} $ 拉斯维加斯市的高层区域。

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