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Automated threshold selection for a constant false alarm rate

机译:自动阈值选择以常量误报率

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The utility of Constant False Alarm Rate (CFAR) algorithms is that the selection of a detection threshold may be made independently of image intensity. However, wide application of the algorithms shows that detection values are highly dependent on scene characteristics. A threshold selection algorithm is presented for a CFAR detection algorithm. Fitting the output of the detection algorithm with a model of a portion of the theoretical results allows for background independent threshold selection.
机译:恒定误报率(CFAR)算法的效用是可以独立于图像强度选择检测阈值。然而,广泛应用算法显示检测值高度依赖于场景特征。提出了一种CFAR检测算法的阈值选择算法。用理论结果的一部分模型拟合检测算法的输出允许背景是独立的阈值选择。

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