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Model based building height retrieval from single SAR images

机译:从单个SAR图像中基于模型的建筑物高度检索

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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:随着星载和机载SAR系统分辨率的提高,雷达遥感的应用已扩展到从城市SAR图像建立3D几何信息检索和重建,这是集结区重建和城市分析的基础。本文主要关注从城市场景的单个高分辨率(HR)SAR图像估计建筑物高度的问题。提出了一种结合建筑物高度估计的图像分割框架的基于模型的方法。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上的观测图像之间的新似然度量。假设平行六面体形状,SAR建筑区域被划分为几个区域。然后,新的似然准则将同时测量分区区域的内部同质性和它们之间的异质性,以实现稳健的高度假设检验。优化是通过模拟退火来完成的,以避免局部最优。在模拟SAR图像数据集上进行的实验结果验证了该方法的有效性。

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