电测与仪表2025，Vol.62Issue(5)：68-75,8.DOI:10.19753/j.issn1001-1390.2025.05.008
一种双分支网络结构的典型电气设备多源图像融合算法
A multi-source image fusion algorithm for typical electrical equipment with dual-branch network structure
摘要
Abstract
With the rapid development of smart grid systems,image fusion technology has received wide attention in order to improve the accurate location of thermal faults.In this paper,the visible and infrared images of sub-station electrical equipment are used as the research object,and the network model is designed by deep learning method with auto-encoder as the backbone network,in which the encoder adopts the designed dual-branch net-work structure of densely connected branch and enhanced branch,one branch is densely connected branch using dense block connection and self-attention mechanism to extract edge and detail features,and the other branch is enhanced branch using a strengthened branch with an improved feature pyramid network(FPN)structure to en-hance the global information.In this paper,two sets of corresponding features are obtained by the dual-branch structure,and the features are fused by the L1-parametric fusion strategy and input the decoder to reconstruct the fused image.After comparing with various methods,the method in the paper verifies the advancement of the algo-rithm in terms of subjective visual evaluation and objective image fusion evaluation indices,in which the objective evaluation indices QMI,SSIM and FMIpixel are 0.567 26,0.593 47 and 0.887 60,respectively,reaching the highest value,which proves that the quality of fused images is improved and applicable to multi-source electrical equipment image fusion.关键词
图像融合技术/双分支网络/电气设备可见光图像和红外图像/图像配准/深度学习Key words
image fusion technology/dual-branch network/visible light image and infrared image of electrical e-quipment/image registration/deep learning分类
动力与电气工程引用本文复制引用
聂启新,肖志云,鲍腾飞,靳旭,高文强,郭浩..一种双分支网络结构的典型电气设备多源图像融合算法[J].电测与仪表,2025,62(5):68-75,8.基金项目
国家自然科学基金资助项目(61661042) （61661042）
内蒙古自治区科技计划项目(2021GG0345) （2021GG0345）
内蒙古自治区自然科学基金资助项目(2021MS06020) （2021MS06020）
