Building features extraction based on facade regularities using TerraSAR-X ST data

Jinxing Chen, Bo Zhang, Chao Wang, Hong Zhang, Fan Wu
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Abstract

The grammar of facade structures is often related to regularly distributed signature patterns in high-resolution synthetic aperture radar (SAR) images. Given the structural details in the SAR image, algorithms for building extraction/monitoring should exploit this contextual information for an object-based analysis. In this paper we propose a framework to extract detailed high rise building features including building masks, orientations and stories. We developed a top-down approach which consists of processing at three levels, namely image level, region-of-interest (ROI) level and storey level. The analysis follows assumptions on the intensity distribution, the linear arrangement, and the regularity of point-like signatures. The proposed approach is validated using a high resolution staring spotlight TerraSAR-X image. A preliminary experiment for change detection using the extracted building features is also studied in this paper.
基于TerraSAR-X ST数据立面规律的建筑特征提取
在高分辨率合成孔径雷达(SAR)图像中,立面结构的语法通常与规则分布的特征模式有关。考虑到SAR图像中的结构细节,建筑提取/监控算法应该利用这些上下文信息进行基于对象的分析。在本文中,我们提出了一个框架来提取详细的高层建筑特征,包括建筑掩模、朝向和楼层。我们开发了一种自上而下的方法,包括三个层次的处理,即图像级,感兴趣区域(ROI)级和层级。分析遵循了强度分布、线性排列和点状特征的规则性假设。使用高分辨率凝视聚焦TerraSAR-X图像验证了所提出的方法。本文还研究了利用提取的建筑物特征进行变化检测的初步实验。
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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