舰船电子工程2026，Vol.46Issue(4)：32-38,7.DOI:10.3969/j.issn.1672-9730.2026.04.007
基于自适应边缘引导网络的遥感影像道路分割
Road Segmentation of Remote Sensing Image Based on Adaptive Edge Guided Network
摘要
Abstract
Aiming at the problems of spatial feature and edge detail information loss,weak anti-interference ability in road segmentation algorithms in remote sensing images,a remote sensing image road semantic segmentation method based on adaptive edge guidance network is proposed.This method is based on an improved U-net network framework,combined with edge detection attention mechanism,target boundaries are used as assistance to guide the network model to automatically adjust learning parame-ters and adaptively capture effective feature information of interest.At the same time,multi-scale feature fusion technology is adopt-ed to aggregate information from multiple kernels to achieve adaptive receptive field size for neurons,and to adaptively screen useful feature information under different receptive fields from both channel and spatial dimensions,highlighting road edge features and improving the accuracy of road classification.This method is tested on the publicly available dataset of Deep Globe Road Dataset,and the Dice segmentation coefficient is 0.867,Jaccard segmentation coefficient is 0.765,accuracy is 97.26%,precision is 86.73%,recall is 79.23%,and average IoU is 78.15%.The experimental results show that this method can effectively improve the accuracy of road segmentation in remote sensing images.关键词
遥感影像/边缘引导/语义分割/注意力机制/多尺度特征Key words
remote sensing image/edge guidance/semantic segmentation/attention mechanism/multi-scale feature分类
信息技术与安全科学引用本文复制引用
万加龙,乔文昇..基于自适应边缘引导网络的遥感影像道路分割[J].舰船电子工程,2026,46(4):32-38,7.基金项目
国家自然科学基金项目(编号:62303433)资助. （编号:62303433）
