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Building extraction based on stereo analysis of high-resolution SAR images taken from orthogonal aspect directions

机译:基于从垂直方面方向拍摄的高分辨率SAR图像的立体分析的建筑物提取

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In this paper high-resolution SAR images of an urban scene are analyzed in order to infer buildings and their heights from the different layover effects in perpendicular taken views. Due to the strong dependence of the appearance of objects on the lighting and viewing direction, it is unlikely that a simple image-matching method would succeed. Instead, higher level object matching is proposed. Here, a knowledge-based approach is applied, a production system. The images are analyzed separately for the presence of certain object groups and their characteristics frequently appearing on buildings, such as salient rows, rectangular structures, or symmetries. The stereo analysis is then accomplished locally by means of productions that combine and match these image objects and infer the height. The approach is tested using real SAR data of an urban scene.
机译:在本文中,分析了城市场景的高分辨率SAR图像,以便从垂直拍摄的视图中的不同停留效果推断建筑物及其高度。由于物体的外观强烈依赖于照明和观察方向,因此简单的图像匹配方法不太可能成功。相反,提出了更高级别的对象匹配。在这里,采用了一种基于知识的方法,即生产系统。分别分析图像中是否存在某些对象组及其在建筑物上经常出现的特征,例如显着的行,矩形结构或对称性。然后,通过组合和匹配这些图像对象并推断出高度的作品,在本地完成立体分析。使用城市场景的实际SAR数据测试了该方法。

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