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The Fusion of Morphological and Contextual Information for Building Detection from Very High-Resolution SAR Images

机译:形态学和上下文信息的融合,用于从高分辨率SAR图像进行建筑物检测

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Nowadays, very high-resolution synthetic aperture radar (VHR SAR) images are available for interpretation of the built-up area. Buildings are one of the most important parts of the urban area, and in this paper a new method for building detection from a single SAR image is proposed. First, the contextual information of the buildings, such as double bounce, layover and shadow areas are extracted. Using these features, a set of primary detection is made. Second, morphological profiles (MP), with different structural elements (SE), are utilized to build a differential morphological profile (DMP) that provides the building structural information. This structural information is used to make a secondary detection set of building candidates. The final detection result is made by fusion of these two sets. Performance evaluation of the proposed method is reported by the implementation of the method on two different real TerraSAR-X images. The results show that the proposed method has a high detection rate (DR), while the false alarm rate (FAR) is low.
机译:如今,非常高分辨率的合成孔径雷达(VHR SAR)图像可用于解释建筑区域。建筑物是市区最重要的部分之一,在本文中,提出了一种从单个SAR图像进行建筑物检测的新方法。首先,提取建筑物的上下文信息,例如双重反弹,中途停留和阴影区域。使用这些功能,可以进行一组主要检测。第二,利用具有不同结构元素(SE)的形态特征(MP)来构建提供建筑物结构信息的差异形态特征(DMP)。该结构信息用于构建建筑物候选的辅助检测集。最终的检测结果是通过将这两个集合融合而得出的。通过在两个不同的真实TerraSAR-X图像上实施该方法,报告了该方法的性能评估。结果表明,该方法具有较高的检测率(DR),而虚警率(FAR)较低。

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