无人机遥感图像目标检测技术研究综述  

Review of Object Detection Technology for Remote Sensing Images from Unmanned Aerial Vehicles(UAVs)

作　　者：王长龙 冀鲸宇 赵月飞 林志龙 马晓琳 WANG Changlong;JI Jingyu;ZHAO Yuefei;LIN Zhilong;MA Xiaolin(Shijiazhuang Campus,Army Engineering University of PLA,Shijiazhuang 050003,China)

机构地区：[1]陆军工程大学石家庄校区,河北石家庄050003

出　　处：《陆军工程大学学报》2025年第1期35-46,共12页Journal of Army Engineering University of PLA

摘　　要：目标检测技术在无人机遥感图像方面具有巨大发展潜力。为了有针对性地设计出适合遥感图像的目标检测算法,需要准确把握当前各类算法的优势及局限,探索新的解决策略。本文对基于传统技术和深度学习的目标检测方法进行了全面系统的分析,并将各类算法进行了对比;总结了常用的遥感图像数据集及目标检测算法的评价指标;针对遥感图像目标检测中目标较小、含有遮挡物以及背景环境复杂等关键问题,深入剖析了现有方法在处理这些难点时所面临的挑战;鉴于遥感图像的背景环境以及特性,从5个方面探讨了当前算法可能的改进方向,为无人机遥感图像目标检测技术的发展提供了参考。Object detection technology has great potential for progress in the field of UAV remote sensing images.In order to design object detection algorithms suitable for remote sensing images,it is necessary to accurately grasp the advantages and disadvantages of the current algorithms and explore new solutions.Firstly,this paper conducts a comprehensive and systematic analysis of object detection detection methods based on traditional techniques and deep learning,and compares the various algorithms.Secondly,it summarizes the commonly used remote sensing image datasets and evaluation metrics for object detection detection algorithms.Thirdly,to address the key challenges in remote sensing image object detection,such as small target size,occlusion,and complex background environments,the paper deeply analyzes the difficulties faced by the existing methods in handling these issues.Finally,considering the background environments and characteristics of remote sensing images,the paper discusses the potential improvement directions for the current algorithms from five aspects,providing a reference for the development of object detection technology in unmanned aerial vehicle(UAV)remote sensing images.

关 键 词：无人机遥感图像 目标检测 数据集 评价指标 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]