红外技术2026，Vol.48Issue(4)：494-502,9.
基于动态金字塔和注意力机制的红外图像去噪
Infrared Image Denoising Based on Dynamic Pyramid and Attention Mechanism
摘要
Abstract
Infrared images are widely utilized across various applications;however,sensor-induced background noise often results in a low signal-to-noise ratio and poor visual quality.To address issues such as incomplete noise removal,high computational cost,and loss of texture features in existing denoising algorithms,this study proposes an infrared image denoising method based on a dynamic pyramid structure and attention mechanisms.First,multi-scale image features are extracted using a pyramid architecture.Second,a dynamic correction and fusion mechanism is introduced to enhance the network's capability for multi-scale feature integration.Finally,a local-context attention block is designed to enhance the restoration of both local details and contextual information.Experimental results on both visible-light and infrared image datasets demonstrate that the proposed algorithm effectively removes noise,preserves texture details,avoids artifacts and speckle noise,and reduces GFLOPS by 65%compared with the NAFNet method.关键词
红外图像去噪/金字塔网络/注意力机制/动态卷积Key words
infrared image denoising/pyramid network/attention mechanism/dynamic convolution分类
信息技术与安全科学引用本文复制引用
吴敬芳,张涛..基于动态金字塔和注意力机制的红外图像去噪[J].红外技术,2026,48(4):494-502,9.基金项目
船舶总体性能创新研究开放基金(A44221001) （A44221001）
武器装备研发项目. （）
