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ISTDet: An efficient end-to-end neural network for infrared small target detection
Infrared Physics & Technology ( IF 3.3 ) Pub Date : 2021-01-26 , DOI: 10.1016/j.infrared.2021.103659
Moran Ju , Jiangning Luo , Guangqi Liu , Haibo Luo

Infrared small target detection has made many breakthroughs in early warning, guidance and battlefield intelligence. However, infrared small target occupies less pixels and lacks color and texture features, which makes infrared small target detection a challenging subject. To achieve the infrared small target detection, an efficient end-to-end network ISTDet is proposed in this paper. ISTDet mainly consists of two modules, including image filtering module and infrared small target detection module. The image filtering module is proposed to obtain the confidence map, aiming to enhance the response of infrared small targets and suppress the response of background. The infrared small target detection module takes the infrared image activated by the confidence map as input, aiming to speculate the category and position of the infrared small targets. Multi-task loss function is used to train the ISTDet in an end-to-end way. Finally, we do comparative experiments on five infrared small target sequences to demonstrate the detection performance of ISTDet. The results show ISTDet has better performance for infrared small target detection compared with other detectors.



中文翻译:

ISTDet:用于红外小目标检测的高效端到端神经网络

红外小目标检测在预警,制导和战场情报方面取得了许多突破。然而,红外小目标占据较少的像素并且缺乏颜色和纹理特征,这使得红外小目标检测成为具有挑战性的主题。为了实现红外小目标检测,本文提出了一种高效的端到端网络ISTDet。ISTDet主要由两个模块组成,包括图像过滤模块和红外小目标检测模块。提出了图像滤波模块来获取置信度图,以增强红外小目标的响应并抑制背景响应。红外小目标检测模块将通过置信度图激活的红外图像作为输入,以推测红外小目标的类别和位置。多任务丢失功能用于以端到端的方式训练ISTDet。最后,我们对五个红外小目标序列进行了对比实验,以证明ISTDet的检测性能。结果表明,与其他探测器相比,ISTDet在红外小目标探测方面具有更好的性能。

更新日期:2021-02-03
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