北京航空航天大学学报2026，Vol.52Issue(6)：1955-1964,10.DOI:10.13700/j.bh.1001-5965.2024.0289
基于多源图像融合的无人机航拍舰船目标识别方法
Ship target recognition method based on multi-source image fusion for unmanned aerial vehicle aerial photography
摘要
Abstract
A multi-source ship image fusion recognition method is proposed for unmanned aerial vehicle aerial photography of multi-source ship images.In the face of many interferences in real scenes,pixel level fusion is adopted to fuse infrared and visible light ship images,and then perform target recognition.It can improve the algorithm's interpretability and lessen the network's reliance on samples as compared to feature level recognition techniques.This article focuses on solving the pixel offset caused by different sensor parameters.To eliminate the distortion and artifacts that traditional picture registration can readily cause,image registration has been turned into end-to-end feature alignment.A multi-source ship image fusion recognition network is proposed,which consists of a cross modulation feature extraction module,a feature dynamic alignment module,a multi granularity feature refinement module,and a pyramid feature fusion module.It can fully integrate the features and texture details of different modal images,effectively improving the recognition performance of ship targets.The approach described in this study has demonstrated great interpretability for multi-source images,good fusion performance,and high accuracy and robustness in recognizing ship targets through experimental verification.关键词
无人机/多源舰船图像/融合识别/像素级融合/像素偏移Key words
unmanned aerial vehicle/multi source ship images/fusion recognition/pixel level fusion/pixel offset分类
航空航天引用本文复制引用
姜杰,闫文君,刘凯,张立民..基于多源图像融合的无人机航拍舰船目标识别方法[J].北京航空航天大学学报,2026,52(6):1955-1964,10.基金项目
国家自然科学基金(62371465) （62371465）
山东省青创团队(2022kj084) （2022kj084）
山东省自然科学基金(ZR2020QF010) National Natural Science Foundation of China(62371465) （ZR2020QF010）
Shandong Province Youth Innovation Team(2022kj084) （2022kj084）
Shandong Provincial Natural Science Foundation(ZR2020QF010) （ZR2020QF010）
