海洋舰船目标红外检测技术研究  

Research on infrared detection technology of Marine ship targets

作　　者：贾春荣 杨帆 高建鑫 沈萌萌 卓越 邸志刚 JIA Chunrong;YANG Fan;GAO Jianxin;SHEN Mengmeng;ZHUO Yue;DI Zhigang(North China University of Science and Technology,Tangshan Hebei 063210,China)

机构地区：[1]华北理工大学电气工程学院,河北唐山063210

出　　处：《激光杂志》2024年第6期13-20,共8页Laser Journal

基　　金：河北省教育厅科学技术研究项目(No.ZD2021332);华北理工大学培育基金(No.SP201502)。

摘　　要：舰船作为海上交通的核心以及海洋战争中重要的军事目标,其检测和识别在民用及军事领域都具有极其深远的现实意义,但复杂的海洋环境使得舰船目标检测存在诸多困难。红外成像及目标检测在复杂海况下有着优良的适用性,针对当下舰船目标检测需求,概述了舰船目标红外检测技术发展的现状,分析了红外图像预处理方法与基于深度学习的舰船目标检测算法,对比了主流方法的优缺点,最后对研究现状与技术改进做了系统性的归纳梳理,并对其未来发展趋势进行了展望。As the core of maritime transportation and an important military target in maritime warfare,the detec-tion and recognition of ships have extremely profound practical significance in both civilian and military fields.Howev-er,the complex marine environment makes ship target detection difficult.Infrared imaging and target detection have excellent applicability in complex sea conditions.In response to the current demand for ship target detection,this pa-per summarizes the current development status of ship target infrared detection technology,analyzes infrared image pre-processing methods and ship target detection algorithms based on deep learning,compares the advantages and disad-vantages of mainstream methods,and finally systematically summarizes and sorts out the research status and technologi-cal improvements,And prospects for its future development trends were presented.

关 键 词：红外图像预处理 非均匀性校正 神经网络 舰船目标检测 深度学习 

分 类 号：TN247[电子电信—物理电子学]