舰船电子工程2025，Vol.45Issue(7)：32-35,85,5.DOI:10.3969/j.issn.1672-9730.2025.07.008
基于注意力机制和扩增感受野的真实图像盲去噪
Real Image Blind Denoising Based on Attentional Mechanism and Amplified Receptive Field
杜延墨 1沈三民 1张炳玮1
作者信息
- 1. 中北大学仪器科学与动态测试教育部重点实验室 太原 030051
- 折叠
摘要
Abstract
In order to achieve a good balance between spatial information and contextual semantic information in image denois-ing task,a real image denoising network based on attention mechanism and amplified receptive field is proposed.The network is composed of noise estimation and non-blind denoising.The receptive field is expanded by kernel dilation,and the attention mecha-nism is embedded in the forward connection and the horizontal skip connection to capture task-related feature information efficient-ly,and the contextual semantic information is retained to a certain extent.The linear combination of asymmetric loss and total varia-tion loss is used as the loss function to deal with the complex and variable noise types in real images and improve the generalization ability of the model.The experimental results show that the SSIM of the proposed method on SIDD and DND data sets reaches 88%and 95%,and the PSNR reaches 35.48 dB and 39.16 dB.Therefore,it has a good image denoising effect.关键词
图像去噪/注意力机制/扩张卷积/深度学习Key words
image denoising/attention mechanism/dilated convolution/deep learning分类
信息技术与安全科学引用本文复制引用
杜延墨,沈三民,张炳玮..基于注意力机制和扩增感受野的真实图像盲去噪[J].舰船电子工程,2025,45(7):32-35,85,5.
