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首页> 外文期刊>Geoscience and Remote Sensing Letters, IEEE >Target Detection in High-Resolution SAR Images via Searching for Part Models
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Target Detection in High-Resolution SAR Images via Searching for Part Models

机译:通过搜索零件模型检测高分辨率SAR图像中的目标

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摘要

In high-resolution synthetic aperture radar (SAR) images, targets are often spatially spread, and some separated regions of one target may be detected as different potential targets. The target should be represented by a part model to combine the separated regions into one target. In this letter, a part often means a separated region, and the part model obtains a hierarchical combination of the other parts. Moreover, the bottom hierarchy consists of strong scatters in the local SAR image, which are searched based on compressed intensities. The middle hierarchy consists of parts, which are generated based on connectivity and similarity of scatters in the bottom hierarchy. The top hierarchy delineates the relationship of parts in the middle hierarchy. A search method is designed based on the different features of the elements in each hierarchy. Consequently, the proposed algorithm combines different traits of targets to improve detection, and unites the separated regions of one target in the top hierarchy. This algorithm is validated by SAR images with different resolutions and scenes. scatters connectivity
机译:在高分辨率合成孔径雷达(SAR)图像中,目标通常在空间上分布,并且一个目标的某些分离区域可能被检测为不同的潜在目标。目标应由零件模型表示,以将分离的区域组合为一个目标。在这封信中,零件通常表示分隔的区域,零件模型获得其他零件的层次组合。此外,底部层次结构由局部SAR图像中的强散射组成,这些散射是基于压缩强度进行搜索的。中间层次结构由多个部分组成,这些部分是根据底层层次结构中的散布的连通性和相似性生成的。顶层层次结构描述了中间层次结构中各部分的关系。根据每个层次结构中元素的不同特征来设计搜索方法。因此,提出的算法结合了目标的不同特征以提高检测效率,并在顶层层次结构中统一了一个目标的分离区域。该算法通过具有不同分辨率和场景的SAR图像进行了验证。分散连接

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