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Infrared dim target detection based on visual attention

机译:基于视觉注意力的红外昏暗目标检测

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摘要

Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. Based on human visual attention mechanisms, an automatic detection algorithm for infrared dim target is presented. After analyzing the characteristics of infrared dim target images, the method firstly designs Difference of Gaussians (DoG) filters to compute the saliency map. Then the salient regions where the potential targets exist in are extracted by searching through the saliency map with a control mechanism of winner-take-all (WTA) competition and inhibition-of-return (IOR). At last, these regions are identified by the characteristics of the dim IR targets, so the true targets are detected, and the spurious objects are rejected. The experiments are performed for some real-life IR images, and the results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.
机译:准确,快速地检测出红外暗淡目标对红外精确制导,预警,视频监控等具有十分重要的意义。基于人类的视觉注意力机制,提出了一种红外暗淡目标的自动检测算法。在分析了红外暗淡目标图像的特征之后,该方法首先设计了高斯差分(DoG)滤波器来计算显着性图。然后,通过使用胜者通吃(WTA)竞争和收益抑制(IOR)的控制机制在显着性图中进行搜索,提取出可能存在目标的显着区域。最后,通过暗淡红外目标的特征来识别这些区域,因此可以检测到真实目标,并拒绝伪造目标。对一些真实的红外图像进行了实验,结果证明了该方法具有令人满意的检测效果和鲁棒性。同时,具有较高的检测效率,可用于实时检测。

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