Detecting slowly moving infrared targets using temporal filtering and association strategy  

作　　者：Jing-li GAO Cheng-lin WEN Zhe-jing BAO Mei-qin LIU 

机构地区：[1]College of Electrical Engineering,Zhejiang University,Hangzhou 310027,China [2]School of Automation,Hangzhou Dianzi University,Hangzhou 310018,China [3]College of Electrical Engineering,Henan University of Technology,Zhengzhou 350001,China [4]College of Software Engineering,Pingdingshan University,Pingdingshan 467000,China

出　　处：《Frontiers of Information Technology & Electronic Engineering》2016年第11期1176-1185,共10页信息与电子工程前沿（英文版）

基　　金：the National Natural Science Foundation of China(Nos.61273170 and 61503206);the Zhejiang Provincial Natural Science Foundation of China(Nos.LZ16F030002 and LZ15F030001)

摘　　要：The special characteristics of slowly moving infrared targets, such as containing only a few pixels,shapeless edge, low signal-to-clutter ratio, and low speed, make their detection rather difficult, especially when immersed in complex backgrounds. To cope with this problem, we propose an effective infrared target detection algorithm based on temporal target detection and association strategy. First, a temporal target detection model is developed to segment the interested targets. This model contains mainly three stages, i.e., temporal filtering,temporal target fusion, and cross-product filtering. Then a graph matching model is presented to associate the targets obtained at different times. The association relies on the motion characteristics and appearance of targets,and the association operation is performed many times to form continuous trajectories which can be used to help disambiguate targets from false alarms caused by random noise or clutter. Experimental results show that the proposed method can detect slowly moving infrared targets in complex backgrounds accurately and robustly, and has superior detection performance in comparison with several recent methods.The special characteristics of slowly moving infrared targets, such as containing only a few pixels,shapeless edge, low signal-to-clutter ratio, and low speed, make their detection rather difficult, especially when immersed in complex backgrounds. To cope with this problem, we propose an effective infrared target detection algorithm based on temporal target detection and association strategy. First, a temporal target detection model is developed to segment the interested targets. This model contains mainly three stages, i.e., temporal filtering,temporal target fusion, and cross-product filtering. Then a graph matching model is presented to associate the targets obtained at different times. The association relies on the motion characteristics and appearance of targets,and the association operation is performed many times to form continuous trajectories which can be used to help disambiguate targets from false alarms caused by random noise or clutter. Experimental results show that the proposed method can detect slowly moving infrared targets in complex backgrounds accurately and robustly, and has superior detection performance in comparison with several recent methods.

关 键 词：Temporal target detection Slowly moving targets Graph matching Target association 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TN215[自动化与计算机技术—计算机科学与技术]