液晶与显示2025，Vol.40Issue(10)：1520-1531,12.DOI:10.37188/CJLCD.2025-0131
基于细节自适应和浅层引导的遥感影像道路提取
Road extraction from remote sensing images based on shallow guidance and detail-adaptive
摘要
Abstract
To address two key challenges—namely,the multi-scale and multi-directional nature of roads and the frequent loss of fine-grained details,we propose a novel remote sensing road extraction network based on detail-adaptive and shallow feature guidance.Firstly,we design a shallow feature-guided attention module,which integrates strip convolutions,attention mechanisms,and shallow feature guidance to enhance the reconstruction of detailed information.Then,a multi-scale and multi-directional feature fusion module is developed,leveraging Gabor convolutions,local pooling,and global directional pooling to improve the representation of road features at various scales and directions.Finally,a detail-adaptive enhancement module is constructed using Gaussian filtering,interpolation,serpentine convolution,and standard convolution,which adaptively enhances the detailed information.The proposed network achieves F1-scores and IoU values of 74.62%and 62.38%on the CHN6-CUG dataset and 77.86%and 65.17%on the Massachusetts dataset,outperforming eight existing methods by at least 1.41%and 1.32%and 1.04%and 0.88%,respectively.Compared with other advanced methods,the proposed model demonstrates superior performance in road extraction tasks,maintaining high extraction accuracy while having a lower parameter count,showing a good balance between performance and efficiency.关键词
遥感影像/道路提取/多尺度/注意力/多向卷积Key words
remote sensing image/road extraction/multi-scale/attention/multi-directional convolution分类
信息技术与安全科学引用本文复制引用
翟保明,邵攀,熊彪,漆琛崴,高玉倩,李净漪..基于细节自适应和浅层引导的遥感影像道路提取[J].液晶与显示,2025,40(10):1520-1531,12.基金项目
国家自然科学青年基金(No.41901341) （No.41901341）
湖北省自然科学基金面上项目(No.2024AFB867 （）
No.2024AFB217) （）
自然资源部地理国情监测重点实验室开放基金项目(No.2025NGCM03)Supported by National Natural Science Foundation of China(No.41901341) （No.2025NGCM03）
Natural Science Foundation of Hubei Province(No.2024AFB867 （）
No.2024AFB217) （）
Open Fund Project of the Key Laboratory of Geo-Environmental Monitoring,Ministry of Natural Resources(No.2025NGCM03) （No.2025NGCM03）
