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A novel spatio-temporal saliency approach for robust dim moving target detection from airborne infrared image sequences

机译:一种新颖的时空显着性方法,用于从机载红外图像序列中进行鲁棒的暗淡运动目标检测

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摘要

Dim moving target detection from infrared image sequences, which lags behind the visual perception ability of humans, has attracted considerable interest from researchers due to its crucial role in airborne surveillance systems. This paper proposes a novel spatio-temporal saliency model to cope with the infrared dim moving target detection problem. Based on a closed-form solution derived from regularized feature reconstruction, a local adaptive contrast operation is proposed, whereby the spatial saliency map and the temporal saliency map can be calculated on the spatial domain and the temporal domain. In order to depict the motion consistency characteristic of the moving target, this paper also proposes a transmission Operation to generate-the trajectory prediction map. The fused result of the spatial saliency map, the temporal saliency map, and the trajectory prediction map is called the "spatio-temporal saliency map" in this paper, from which the target of interest can be easily segmented. A diverse test dataset comprised of three infrared image sequences under different backgrounds was collected to evaluate the proposed model; and extensive experiments confirmed that the proposed spatio-temporal saliency model can achieve much better detection performance than the state-of-the-art approaches. (C) 2016 Elsevier Inc. All rights reserved.
机译:由于其在机载监视系统中的关键作用,根据红外图像序列进行的昏暗运动目标检测(其落后于人类的视觉感知能力)已引起研究人员的极大兴趣。本文提出了一种新颖的时空显着性模型来解决红外暗淡运动目标检测问题。基于从正则化特征重构得到的闭式解,提出了一种局部自适应对比操作,可以在空间域和时间域上计算空间显着图和时间显着图。为了描述运动目标的运动一致性特征,本文还提出了一种传输操作来生成轨迹预测图。空间显着图,时间显着图和轨迹预测图的融合结果在本文中被称为“时空显着图”,从中可以轻松地分割感兴趣的目标。收集了由不同背景下的三个红外图像序列组成的多样化测试数据集,以评估所提出的模型;大量的实验证实,所提出的时空显着性模型可以比最新方法获得更好的检测性能。 (C)2016 Elsevier Inc.保留所有权利。

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