红外技术2026，Vol.48Issue(1)：62-69,8.
FDnet:基于频域分解网络的红外小目标检测
FDnet:Frequency Decomposition Network for Infrared Small Target Detection
摘要
Abstract
In recent years,the detection of small infrared targets,which lack texture and shape information,in the presence of complex background clutter has become a significant challenge.Traditional model-driven approaches exhibit limited feature-learning and representation capabilities,thus showing poor adaptability to diverse scenarios.Most deep-learning-based detection methods rely on deep network architectures to extract features;such architectures may lead to the loss of fine-grained texture information in deeper layers and are thus less effective for small infrared target detection.To address these challenges,we propose a frequency decomposition network(FDnet)that follows the design principle of decomposing an image in the frequency domain and processing different frequency components separately.Specifically,FDnet first employs a high-frequency feature extraction module to decompose the input image into high-and low-frequency components.These components are then processed by two separate branches to extract boundary and semantic information.To facilitate interaction between the two branches,a spatial information aggregation(SIA)module is introduced,enabling high-frequency features to guide the low-frequency branch.Furthermore,considering the sparsity of high-frequency components,a spatially sparse self-attention mechanism(SSAM)is incorporated into the high-frequency branch to better capture spatial attention,whereas a channel-wise attention mechanism(CAM)is embedded in the low-frequency branch to model global channel dependencies.These components operate collectively to enhance a network's perception of meaningful targets.Experimental results on public datasets demonstrate that the proposed method achieves high detection accuracy with significantly fewer parameters compared to other state-of-the-art approaches.关键词
红外图像/弱小目标检测/注意力机制/图像分割Key words
infrared images/small target detection/attention mechanism/image segmentation分类
信息技术与安全科学引用本文复制引用
杜妮妮,叶文亚,刘烨,徐生..FDnet:基于频域分解网络的红外小目标检测[J].红外技术,2026,48(1):62-69,8.基金项目
宁波市科技计划项目(2024S076) （2024S076）
宁波市交通运输科技计划项目(202216). （202216）
