计算机技术与发展2026，Vol.36Issue(9)：37-44,8.DOI:10.20165/j.cnki.ISSN1673-629X.2026.0079
基于改进视觉RWKV的红外图像小目标检测算法
A Novel Method for Infrared Small Target Detection Based on Improved Visual RWKV
摘要
Abstract
Infrared small target detection has the advantages of low cost,non-contact sensing,and passive imaging,but it still faces signif-icant challenges under complex background conditions,such as small target size,low contrast,and strong background interference.To ad-dress the limited global modeling capability of convolutional neural network-based methods and the high computational complexity of Transformer-based approaches,we explore the introduction of the RWKV architecture into infrared small target detection and propose an improved visual RWKV-based detection algorithm,termed RWKV-ISTD.The proposed network adopts a dual-branch structure to sepa-rately extract local and global features.An improved visual RWKV auxiliary encoder is employed to model global contextual informa-tion,while a residual convolution-based main encoder is used to effectively capture local detail features.Considering the characteristics of infrared small target images,a novel multi-scale shift module combined with wavelet transform is designed to enhance multi-frequency feature representation during global feature extraction.In addition,an improved feature fusion module is introduced to enable deep inter-action between local and global features.Extensive experiments conducted on the NUAA-SIRST and IRSTD-1K public datasets demon-strate that the proposed method effectively improves infrared small target detection performance under complex backgrounds,while exhibi-ting advantages in model complexity control.These results indicate that the proposed approach achieves a reasonable balance between de-tection accuracy and computational efficiency,providing a feasible solution for infrared small target detection tasks.关键词
红外小目标检测/RWKV/特征融合/多尺度移位/双分支编码Key words
infrared small target detection/receptance weight key value/feature fusion/multi-scale shifting/dual-branch encoding分类
信息技术与安全科学引用本文复制引用
贾桂敏,马宇驰,陈涛..基于改进视觉RWKV的红外图像小目标检测算法[J].计算机技术与发展,2026,36(9):37-44,8.基金项目
天津市教委科研计划项目(2022KJ062) （2022KJ062）
