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A robust approach for detecting infrared small dim targets

机译:一种用于检测红外小暗目标的可靠方法

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摘要

A new detection algorithm of dim moving targets in the IR image sequences is presented. The images consist mainly of sensor noise, drifting background clutter and low contrast targets. So it is difficult to provide reliable detection in just a single frame. This algorithm adopts multi-scale gradient to suppress the clutter according to its spatial distribution feature. Then the recursive maximum similarity (RMS) filter is used to accumulate targets energy in temporal domain. The advantage of the algorithm is that it realizes the enhancement of the target gradient feature and clutter suppressing in the same time. The results show that the algorithm can effectively detect the real small dim targets even if there is strong clutter influence.
机译:提出了一种新的红外图像序列中暗淡运动目标的检测算法。图像主要由传感器噪声,漂移的背景杂波和低对比度目标组成。因此,难以仅在单个帧中提供可靠的检测。该算法根据空间分布特征采用多尺度梯度抑制杂波。然后,使用递归最大相似度(RMS)滤波器在时域中累积目标能量。该算法的优点是可以同时实现目标梯度特征的增强和杂波抑制。结果表明,即使在杂波影响较大的情况下,该算法也能有效地检测出真实的弱小目标。

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