红外技术2026，Vol.48Issue(2)：184-192,9.
基于双分支网络的红外与可见光图像融合方法
Infrared and Visible Image Fusion Method Based on a Dual-branch Network
摘要
Abstract
In the fields of infrared and visible image fusion,traditional image fusion methods only use the same convolution operation to extract local features,which may lead to the absence of semantic and texture detail information in the fused results.Therefore,this paper proposes a two-branch network approach for image fusion.First,to improve the ability of the model in describing low-level details and high-level semantics of the image,the source image is input into the two-branch structure of the encoder,and detail information is extracted separately but in parallel with semantic information.Second,gradient residual dense block-reinforced coding network was used to enhance the model's ability to describe fine-grained information.The feature fusion network uses the strategy of bilateral bootstrap aggregation layer for the deep feature fusion of the two branches.Finally,the proposed method was compared with seven other fusion methods on the TNO public dataset and experimentally ablated.The results show that the fused images obtained by the proposed method are rich in information,more suitable for human visual perception,and have significant advantages in objective indices such as peak signal-to-noise ratio,sum of difference correlation,and visual information fidelity.关键词
图像融合/特征提取/红外图像/可见光图像Key words
image fusion/feature extraction/infrared image/visible image分类
信息技术与安全科学引用本文复制引用
石洋,付永红..基于双分支网络的红外与可见光图像融合方法[J].红外技术,2026,48(2):184-192,9.基金项目
陕西省重点研发计划(2023-ZDLGY-24),依托板墙砌筑作业机械化项目支持(20220082). （2023-ZDLGY-24）
