High-rise building detection in dense urban area based on high resolution SAR images

Kan Tang, Bo Liu, Bo Zou
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引用次数: 3

Abstract

Building extraction is an important task for SAR applications in many fields, such as urban planning, population distribution, and environment evaluation. In this paper, we focus on high-rise buildings in complex urban scenarios. The specific characteristics of high-rise building in high resolution (HR) SAR images are analyzed firstly. In particular, we explore the contextual information of bright line features as corner lines and double bounce; extract the textural feature of the periodic patterns appearing in the layover area. Given those signature details, a new algorithm exploit the building information is proposed for high-rise building detection from single SAR images. The algorithm is applied on spotlight TerraSAR-X images of the center districts in Toronto, Canada, which confirm the applicability of the method for variable high-rise buildings.
基于高分辨率SAR图像的密集城区高层建筑检测
建筑物提取是SAR在城市规划、人口分布、环境评价等领域应用的重要内容。本文主要研究复杂城市场景下的高层建筑。首先分析了高层建筑在高分辨率SAR图像中的具体特征。特别地,我们探索了明线特征的上下文信息,如角线和双反弹;提取在停留区域出现的周期性图案的纹理特征。针对这些特征细节,提出了一种利用建筑信息进行高层建筑单幅SAR图像检测的新算法。将该算法应用于加拿大多伦多市中心区的聚光灯TerraSAR-X图像,验证了该算法对可变高层建筑的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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