飞控与探测2026，Vol.9Issue(4)：93-103,11.DOI:10.20249/j.cnki.2096-5974.2026.04.008
恶劣天气下基于可见光与红外融合的车辆目标检测方法
Method of Vehicle Target Detection Based on Visible-Infrared Fusion Under Adverse Weather Conditions
摘要
Abstract
To address the issue of insufficient accuracy and robustness of vehicle target detection in adverse weather conditions such as rain,snow,and fog,a visible-infrared fusion vehicle target de-tection method based on a pseudo-twin architecture is proposed.This method takes YOLOv8 as the basic framework and enhances features through the differentiated design of dual-modal feature extraction branches:the visible light branch embeds the CSDEA module to strengthen the recogni-tion of vehicle texture semantic features;the infrared branch is equipped with the DDPPA module to accurately capture thermal radiation features and suppress noise interference.Meanwhile,a CAFF module is designed to establish precise correlation and bidirectional enhancement of dual-modal features,achieving efficient integration of complementary information.Experimental results on a self-made dual-modal dataset show that the proposed method significantly outperforms existing public dual-modal algorithms in terms of mAP50 and mAP50:95 metrics,demonstrating significant advantages in small target detection,occluded target recognition,and anti-interference in low visibility scenarios,effectively improving the accuracy and stability of vehicle target detec-tion in adverse weather conditions.关键词
车辆目标检测/双模态融合/伪孪生架构Key words
vehicle target detection/dual-modal fusion/pseudo-siamese architecture分类
信息技术与安全科学引用本文复制引用
闫佳灿,田甜,赵天明,宋佳民..恶劣天气下基于可见光与红外融合的车辆目标检测方法[J].飞控与探测,2026,9(4):93-103,11.基金项目
国家自然科学基金(42071339) （42071339）
