湖南大学学报（自然科学版）2025，Vol.52Issue(12)：164-175,12.DOI:10.16339/j.cnki.hdxbzkb.2025295
基于多尺度特征的渐进式红外偏振图像融合方法
Progressive Infrared Polarization Image Fusion Method Based on Multi-scale Features
摘要
Abstract
In complex environments,traditional infrared detection methods are severely limited,necessitating the fusion of polarization technology with infrared technology.This fusion is aimed at existing convolutional neural network methods,which lack the capacity to extract multi-scale information and fuse subnetworks adequately.The objective is to enhance the quality of infrared polarization fusion images and improve the target recognition capability of infrared imaging technology in complex backgrounds.This paper proposes a progressive infrared polarization image fusion method(PIPFuse)based on multi-scale features.Firstly,the feature extraction component employs a semantic extraction module and a multiscale dense block,which are utilized to extract semantically enhanced multiscale depth features.Secondly,to reduce the information loss and enhance the salient information,the fusion subnetwork incorporates a progressive difference information enhancement fusion module for the feature fusion.Finally,the final fused image is obtained by decoding the fused features.In comparison to nine classical image fusion methods,this method demonstrates superior performance in six evaluation indexes.Furthermore,the subjective visualization of the target texture is more distinct and exhibits higher contrast.关键词
红外成像/多尺度特征/渐进策略/图像融合/卷积神经网络Key words
infrared imaging/multi-scale features/incremental strategy/image fusion/convolutional neural net-works分类
信息技术与安全科学引用本文复制引用
陈广秋,魏洲,段锦,黄丹丹..基于多尺度特征的渐进式红外偏振图像融合方法[J].湖南大学学报（自然科学版）,2025,52(12):164-175,12.基金项目
国家自然科学基金重大仪器专项(62127813),National Natural Science Foundation of China(62127813) （62127813）
吉林省科技发展计划项目(20210203181SF),Science and Technology Development Program of Jilin Province(20210203181SF). （20210203181SF）
