红外技术2024，Vol.46Issue(10)：1201-1208,8.
基于多特征的红外双波段目标检测融合算法
Infrared Dual-band Target Detecting Fusion Algorithm Based on Multiple Features
摘要
Abstract
Infrared target detection algorithms play important roles in the military and civilian fields and have been widely studied.However,relatively few studies have been conducted on the use of dual-band images for targeted detection.To fully utilize the advantages of dual-band images in target detection,a fusion algorithm based on multiple features of infrared dual-band images was proposed through an in-depth analysis of the detection results.The proposed fusion algorithm utilizes a deep learning-based multi-feature fusion network to process the detection results of dual-band images,fully mine the feature information of the target,adaptively select the detection results of a single band as the output,and obtain the final decision-level fusion detection results.The experimental results show that,compared with using single-band images for object detection,the proposed infrared dual-band fusion algorithm based on multiple features can effectively utilize information from different bands,improve the detection performance,and fully leverage the advantages of infrared object detection equipment.关键词
目标检测/双波段/决策级融合/卷积神经网络Key words
target detection/dual band/decision level fusion/convolutional neural network分类
计算机与自动化引用本文复制引用
乔志平,黄静颖,王礼贺..基于多特征的红外双波段目标检测融合算法[J].红外技术,2024,46(10):1201-1208,8.
