This paper demonstrates for the first time the potential of explicitly modelling the individual roof surfaces to reconstruct 3-D prismatic building models using spaceborne tomographic synthetic aperture radar (TomoSAR) point clouds. The proposed approach is modular\udand works as follows: it first extracts the buildings via DSM generation and cutting-off the ground terrain. The DSM is smoothed using BM3D denoising method proposed in (Dabov et al., 2007) and a gradient map of the smoothed DSM is generated based on height jumps. Watershed segmentation is then adopted to oversegment the DSM into different regions. Subsequently, height and polygon\udcomplexity constrained merging is employed to refine (i.e., to reduce) the retrieved number of roof segments. Coarse outline of each roof segment is then reconstructed and later refined using quadtree based regularization plus zig-zag line simplification scheme. Finally, height is associated to each refined roof segment to obtain the 3-D prismatic model of the building. The proposed approach is illustrated\udand validated over a large building (convention center) in the city of Las Vegas using TomoSAR point clouds generated from a stack of 25 images using Tomo-GENESIS software developed at DLR.
展开▼
机译:本文首次展示了使用航天层析X射线合成孔径雷达(TomoSAR)点云对单个屋顶表面进行显式建模以重建3-D棱柱形建筑模型的潜力。所提出的方法是模块化的\ udand的工作方式如下:它首先通过DSM生成来提取建筑物并切断地面地形。使用(Dabov et al。,2007)中提出的BM3D去噪方法对DSM进行平滑处理,并根据高度跳跃生成平滑的DSM的梯度图。然后采用分水岭分割将DSM过度分割到不同区域。随后,采用高度和多边形/复杂度受限的合并来精炼(即减少)屋顶段的检索数量。然后重建每个屋顶部分的粗轮廓,然后使用基于四叉树的正则化加之字形线简化方案对其进行精炼。最后,将高度与每个精炼的屋顶部分相关联,以获得建筑物的3-D棱柱模型。使用在DLR开发的Tomo-GENESIS软件从25张图像的堆栈中生成的TomoSAR点云,在拉斯维加斯市的大型建筑物(会议中心)上对提议的方法进行了说明和验证。
展开▼