液晶与显示2025，Vol.40Issue(11)：1688-1699,12.DOI:10.37188/CJLCD.2025-0161
基于时空三维卷积网络的复杂背景下红外弱小目标检测方法
Detection method for infrared dim and small targets under complex backgrounds via a spatio-temporal three-dimensional convolutional network
摘要
Abstract
In the field of aviation early warning,infrared weak target detection technology is crucial for long-range all-weather battlefield perception.Aiming at the problem of low probability of target detection and high false alarm rate caused by a small proportion of pixels and lack of features of infrared dim and small targets under complex background,a detection method for infrared dim and small targets under complex backgrounds via a spatio-temporal three-dimensional convolutional network was proposed.This method proposes a feature extraction backbone network that combines 2D convolution with 3D convolution,and combines spatial texture features and inter-frame motion features to achieve collaborative perception of target structure and temporal changes.According to the characteristics of infrared dim and small targets,a local contrast module is designed as a feature enhancement module to expand the receptive field for feature enhancement;In addition,introducing asymmetric attention mechanism for feature fusion increases the preservation of texture and positional information;Finally,the point regression loss function is used to calculate the detection results.In the experiment,the public data set was compared with the self-built data set,labeled and trained.Experimental results show that compared with the conventional multi-frame target detection network,the improved algorithm has a recall rate improvement of no less than 7.52%and an average precision improvement rate of no less than 6.46%.It can be effectively applied to infrared dim and small target detection in complex backgrounds,and embodies good robustness and adaptability.关键词
红外弱小目标/深度学习/目标检测/时空三维卷积Key words
infrared dim and small target/deep learning/object detection/spatio-temporal three-dimensional convolution分类
信息技术与安全科学引用本文复制引用
李士刚,王维佳,朱圣杰,梁忠毅,马铭阳,王德江,白金成..基于时空三维卷积网络的复杂背景下红外弱小目标检测方法[J].液晶与显示,2025,40(11):1688-1699,12.基金项目
国家自然科学基金(No.62305335) Supported by National Natural Science Foundation of China(No.62305335) （No.62305335）
