一种多分辨率图像目标检测算法  

A Multi-Resolution Image Object Detection Algorithm

作　　者：杜琳琳 张瑜 唐宇 马静静 DU Linlin;ZHANG Yu;TANG Yu;MA Jingjing(Systems Engineering Institute,Academy of Military Science,PLA,Beijing 100010,China)

机构地区：[1]中国人民解放军军事科学院系统工程研究院,北京100010

出　　处：《宇航总体技术》2024年第3期29-36,共8页Astronautical Systems Engineering Technology

摘　　要：为解决航天遥感图像分辨率和目标尺度变化大的挑战,提出了一种基于多分辨率图像的目标检测算法。改进了自适应特征金字塔和轻量级的分类预测模块,通过使用注意力机制,从不同层次的特征图中提取语义信息。引入了一种预测目标尺度的方法,以分析图像中目标的分布和尺度信息。将算法在DOTA(Dataset for Object deTection in Aerial Images)数据集上进行了实验验证,在U-Net(一种基于卷积神经网络的语义分割算法)和ResNet-34(一种深度残差网络)两种不同的主干网络设置下,召回率和检测速度均超过了RPN(Region Proposal Network,区域提议网络)算法。提出的多分辨率图像目标检测算法能有效地提高检测精度,降低计算复杂度。To address the challenges of large image resolution and target scale variations in remote sensing images,this work proposes a target detection algorithm based on multi-resolution images.The adaptive feature pyramid and lightweight classification prediction module are improved.By using attention mechanisms,we extract semantic information from feature maps at different levels,introduce a method for predicting target scale to analyze the distribution and scale information of targets in the images.The algorithm is experimentally validated on the DOTA dataset.With two different backbone network settings,U-Net and ResNet-34,the recall rates and the detection speeds both surpassing the RPN algorithm.The proposed multi-resolution image target detection algorithm effectively improves detection accuracy while reducing computational complexity.

关 键 词：深度神经网络 目标检测 特征金字塔 多尺度目标 多分辨率图像 

分 类 号：V443.5[航空宇航科学与技术—飞行器设计]