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A robust infrared dim target detection method based on template filtering and saliency extraction

机译:基于模板滤波和显着性提取的鲁棒红外弱小目标检测方法

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摘要

Dim target detection in infrared image with complex background and low signal-clutter ratio (SCR) is a significant and difficult task in the infrared target tracking system. A robust infrared dim target detection method based on template filtering and saliency extraction is proposed in this paper. The weighted gray map is obtained from the infrared image to highlight the target which is brighter than its neighbors and has weak correlation with its background. The target saliency map is then calculated by phase spectrum of Fourier Transform, so that the dim target detection could be converted to salient region extraction. The potential targets are finally extracted by combining the two maps. Moreover, position discrimination between targets in the two maps is used to exclude the false alarms and extract the targets. Experimental results on measured images indicate that our method is feasible, adaptable and robust in different backgrounds. The ROC (Receiver Operating Characteristic) curves obtained from the simulated images demonstrate the proposed method outperforms some existing typical methods in both detection rate and false alarm rate, for target detection with low SCR. (C) 2015 Elsevier B.V. All rights reserved.
机译:背景复杂且信号杂波比(SCR)低的红外图像中的弱目标检测是红外目标跟踪系统中一项艰巨而艰巨的任务。提出了一种基于模板滤波和显着性提取的鲁棒红外弱小目标检测方法。从红外图像中获得加权灰度图,以突出显示目标,该目标比其邻居亮并且与背景的相关性较弱。然后通过傅立叶变换的相位谱计算目标显着图,从而将暗淡的目标检测转换为显着区域提取。最终,通过将两个地图结合起来,提取出了潜在目标。此外,两个地图中目标之间的位置辨别用于排除错误警报并提取目标。在实测图像上的实验结果表明,我们的方法在不同背景下是可行的,适应性强的。从仿真图像获得的ROC(接收器工作特性)曲线表明,对于低SCR的目标检测,该方法在检测率和误报率方面均优于一些现有的典型方法。 (C)2015 Elsevier B.V.保留所有权利。

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