液晶与显示2024，Vol.39Issue(6)：822-832,11.DOI:10.37188/CJLCD.2023-0129
基于多尺度残差特征融合的图像去雾算法
Image defogging algorithm based on multi-scale residual feature fusion
摘要
Abstract
Aiming at the problems of dim color,poor visual fidelity and loss of detail features of the image after processing by existing defogging algorithms,this paper proposes an image defogging algorithm based on multi-scale residual feature fusion.Firstly,a multi-scale parallel feature layer is designed to extract image features from different scales to improve the robustness of the network.Then,the residual network connection layer is designed to realize the transmission and connection of information between multiple convolutional layers,improve the feature utilization rate and speed up feature extraction.The depth feature information fusion layer embedded in the attention mechanism is designed to focus on the key information of the image.It can effectively improve the clarity of the image and reduce the background noise interference.Finally,a color correction and enhancement method based on fog removal theory and exposure fusion is designed to solve the problem of dim image color after network defogging.The experimental results show that the proposed defogging enhancement algorithm achieves the peak signal-to-noise ratio(PSNR),structural similarity(SSIM)and mean square error(MSE)of 21.37 dB,82%and 473.6 on the public data sets SOTS,OTS and RTTS,respectively,which effectively improves the image quality degradation caused by foggy weather with better performance.关键词
图像去雾/多尺度卷积/残差连接/注意力机制/图像融合Key words
image defogging/multiscale convolution/residual connection/attention mechanism/image fusion分类
信息技术与安全科学引用本文复制引用
谢欣丹,李晓艳,王鹏,邸若海,孙梦宇,李亮亮..基于多尺度残差特征融合的图像去雾算法[J].液晶与显示,2024,39(6):822-832,11.基金项目
国家自然科学基金(No.62171360) （No.62171360）
陕西省科技厅重点研发计划(No.2022GY-110) （No.2022GY-110）
西安市智能兵器重点实验室(No.2019220514SYS020CG042) （No.2019220514SYS020CG042）
2022年度陕西高校青年创新团队项目 （）
山东省智慧交通重点实验室(筹) （筹）
Supported by National Natural Science Foundation of China(No.62171360) （No.62171360）
Key R&D Program of Shaanxi Science and Technology Department(No.2022GY-110) （No.2022GY-110）
Xi'an Key Laboratory of Intelligent Weapons(No.2019220514SYS020CG042) （No.2019220514SYS020CG042）
2022 Youth Innovation Team Project of Shaanxi University （）
Shandong Intelligent Transportation Key Laboratory(Prepairatory) （Prepairatory）
