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Target/shadow segmentation and aspect estimation in synthetic aperture radar imagery

机译:合成孔径雷达图像中的目标/阴影分割和纵横比估计

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Abstract: This paper discusses algorithms that are useful for the classification of targets in SAR imagery. Two algorithms are presented for segmenting a target region from background clutter; one based on constant false alarm rate detection, and another histogram based technique. The histogram based technique is extended to extract shadow regions associated with a target. A method is then presented for estimating the orientation of segmented targets. These algorithms are applied to SAR imagery from the Lincoln Lab ADTS and MSTAR datasets. The aspect estimate is shown to be superior to estimates obtained from the direction of the axis of least inertia.!14
机译:摘要:本文讨论了可用于SAR图像目标分类的算法。提出了两种从背景杂波中分割目标区域的算法。一种基于恒定的误报率检测,另一种基于直方图的技术。扩展了基于直方图的技术,以提取与目标关联的阴影区域。然后提出了一种用于估计分割目标的方向的方法。这些算法已应用于Lincoln Lab ADTS和MSTAR数据集的SAR图像。纵横比估算值显示出比从最小惯性轴方向获得的估算值还要好。14

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