光学精密工程2024，Vol.32Issue(20)：3085-3098,14.DOI:10.37188/OPE.20243220.3085
融合全局信息与双域注意力机制的光学遥感飞机目标检测
Integrating global information and dual-domain attention mechanism for optical remote sensing aircraft target detection
摘要
Abstract
To address the problem of insufficient detection accuracy of aircraft targets in optical remote sensing images due to complex backgrounds,small targets,and similar appearances among aircraft,an air-craft target detection algorithm was proposed in this paper based on the YOLOv8n model that integrated the global information and the dual-domain attention mechanism in optical remote sensing images.Firstly,the SPPF_Global module was designed to provide a global feature overview through the global maximum pooling layer,which helped the model better distinguish objects from the background in complex environ-ments.Secondly,a dual-domain attention mechanism was proposed to improve the attention to important areas such as wing shape and other distinctive structures through the information guidance of space domain and channel domain,and enhanced the ability to distinguish the nuances of different aircraft models.Final-ly,the parallel path downsampling method and the Powerful-IoU loss function was introduced,and the adaptive penalty factor was used to accelerate the convergence of the model,which improved the recogni-tion ability of the model for small target aircraft and the regression efficiency of the prediction frame.The experimental results show that compared with the original YOLOv8n,the accuracy rate,recall rate,mAP50 and MAP50-95 of the proposed model on the open data set MAR20 are increased by 3.3%,2.6%,3.2%and 2.6%respectively.On the NWPU VHR-10 dataset,the parameters are increased by 5%,5.1%,2.5%and 0.3%respectively,while the number of parameters and the calculation amount are decreased by 6.6%and 3.7%respectively,which proves the efficiency and superiority of the proposed model,and effectively improves the application value of the aircraft target detection algorithm in optical re-mote sensing images.关键词
光学遥感图像/飞机目标检测/YOLOv8/注意力机制/Powerful-IoUKey words
optical remote sensing image/aircraft target detection/YOLOv8/attention mechanism/Powerful-IoU分类
计算机与自动化引用本文复制引用
林珊玲,张雪,陈燕,林坚普,吕珊红,林志贤,郭太良..融合全局信息与双域注意力机制的光学遥感飞机目标检测[J].光学精密工程,2024,32(20):3085-3098,14.基金项目
国家重点研发计划(No.2022YFB3603705) （No.2022YFB3603705）
国家自然科学基金青年基金(No.62101132) （No.62101132）
