计算机科学与探索2025，Vol.19Issue(4)：989-1000,12.DOI:10.3778/j.issn.1673-9418.2403082
跨模态多层特征融合的遥感影像语义分割
Cross-Modal Multi-level Feature Fusion for Semantic Segmentation of Remote Sensing Images
摘要
Abstract
Multimodal semantic segmentation networks can leverage complementary information from different modali-ties to improve segmentation accuracy.Thus,they are highly promising for land cover classification.However,existing multimodal remote sensing image semantic segmentation models often overlook the geometric shape information of deep features and fail to fully utilize multi-layer features before fusion.This results in insufficient cross-modal feature extrac-tion and suboptimal fusion effects.To address these issues,a remote sensing image semantic segmentation model based on multimodal feature extraction and multi-layer feature fusion is proposed.By constructing a dual-branch encoder,the model can separately extract spectral information from remote sensing images and elevation information from normalized digital surface model(nDSM),and deeply explore the geometric shape information of the nDSM.Furthermore,a cross-layer enrichment module is introduced to refine and enhance each layer's features,making full use of multi-layer feature infor-mation from deep to shallow layers.The refined features are then processed through an attention feature fusion module for differential complementarity and cross-fusion,mitigating the differences between branch structures and fully exploiting the advantages of multimodal features,thereby improving the segmentation accuracy of remote sensing images.Experiments conducted on the ISPRS Vaihingen and Potsdam datasets demonstrate mF1 scores of 90.88%and 93.41%,respectively,and mean intersection over union(mIoU)scores of 83.49%and 87.85%,respectively.Compared with current mainstream algorithms,this model achieves more accurate semantic segmentation of remote sensing images.关键词
遥感影像/归一化数字表面模型(nDSM)/语义分割/特征提取/特征融合Key words
remote sensing images/normalized digital surface model(nDSM)/semantic segmentation/feature extraction/feature fusion分类
计算机与自动化引用本文复制引用
李智杰,程鑫,李昌华,高元,薛靖裕,介军..跨模态多层特征融合的遥感影像语义分割[J].计算机科学与探索,2025,19(4):989-1000,12.基金项目
国家自然科学基金(51878536) （51878536）
陕西省住房城乡建设科技计划项目(2020-K09) （2020-K09）
陕西省教育厅协同创新中心项目(23JY038).This work was supported by the National Natural Science Foundation of China(51878536),the Housing and Urban-Rural Construction Science and Technology Plan Project of Shaanxi Province(2020-K09),and the Collaborative Innovation Center Project of Shaanxi Provincial Department of Education(23JY038). （23JY038）
