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Perceptual grouping for automatic detection of man-made structures in high-resolution SAR data

机译:感知分组可自动检测高分辨率SAR数据中的人造结构

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摘要

Modern airborne synthetic aperture radar sensors provide high spatial resolution data. Experimental systems have even achieved decimetre resolution. In such data, many features of urban objects can be identified, which are beyond what has been achieved by radar remote sensing before. An example for the new quality of the appearance of urban man-made objects such as buildings in these data is given and interpreted. The fine level of detail opens the opportunity to reconstruct detailed structures of such objects from SAR data with structural pattern recognition techniques. Artificial intelligence concepts such as production systems provide proper means for this purpose. The feasibility of these methods is demonstrated here. Extended building features such as long thin roof edge lines, groups of salient point scatterers, and symmetric configurations are detected using principles from perceptual grouping and Gestalt psychology. These are good continuation, similarity, proximity and symmetry.
机译:现代机载合成孔径雷达传感器可提供高空间分辨率数据。实验系统甚至达到了分米分辨率。在这样的数据中,可以识别出城市物体的许多特征,这是雷达遥感以前无法实现的。给出并解释了这些数据中城市人造物体(如建筑物)的外观新质量的示例。精细的细节为使用结构模式识别技术从SAR数据重建此类对象的详细结构提供了机会。诸如生产系统之类的人工智能概念为此提供了适当的手段。这些方法的可行性在这里得到证明。利用感知分组和格式塔心理学的原理,可以检测到扩展的建筑特征,例如细长的屋顶边缘线,显着点散射体组和对称配置。这些是良好的连续性,相似性,接近性和对称性。

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