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Model based building height retrieval from single SAR images

机译:基于模型的楼宇高度检索单个SAR图像

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摘要

With the improvements of spaceborne and airborne SAR system resolution, the applications of radar remote sensing has been extended to building 3D geometric information retrieval and reconstruction from urban SAR images, which is the foundation of build-up areas reconstruction and urban analysis. This paper mainly focuses on the problem of building height estimation from a single high resolution (HR) SAR image of urban scenes. A model based method combined with image segmentation framework of building height estimation is proposed. This method optimizes a new likelihood measure between the projection image from 3D geometric model of the buildings and the observed image over the heights hypothesis space. With assumption of the parallelepiped shapes, the SAR building area is partitioned into several regions. The new likelihood criterion then measures both the inner homogeneity of partitioned regions as well as their inter heterogeneity to achieve robust height hypothesis test. The optimization is done by simulated annealing in order to avoid local optimum. The experimental results performed on simulated SAR image data set valid the proposed method.
机译:随着航空发载和空中SAR系统分辨率的改进,雷达遥感的应用已经扩展到建立城市SAR图像的3D几何信息检索和重建,这是建设领域重建和城市分析的基础。本文主要侧重于从城市场景中的单一高分辨率(HR)SAR图像建立高度估计问题。提出了一种基于模型的建筑物高度估计图像分割框架的方法。该方法优化了来自建筑物的3D几何模型的投影图像与高度假设空间的观察图像之间的新似然测量。假设平行六面体形状,SAR建筑面积被划分为几个区域。然后,新的似然标准测量分区区域的内均匀性以及它们间的异质性,以实现鲁棒高度假设试验。通过模拟退火完成优化以避免局部最佳。对模拟SAR图像数据集进行的实验结果有效地提出了该方法。

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