测试技术学报2025，Vol.39Issue(3)：305-312,8.DOI:10.62756/csjs.1671-7449.2025038
基于多尺度信息与HSV空间的图像去沙尘算法
Image Desanding Algorithm Based on Multi-Scale Information and HSV Space
摘要
Abstract
In sandstorm weather,outdoor images often appear blurry,with color cast,etc.,which seriously affects the performance of outdoor computer vision systems.The current sand and dust image enhancement algorithms often suffer from color distortion in large areas of the sky.A multi-scale information and HSV(Hue,Saturation,Value)space-based image denoising algorithm was designed for this purpose.The multi-scale residual denoising module was used to remove sand and dust,and the HSV global adjustment module was used to further adjust the image color cast.Then,an attention mechanism-based feature fusion module was used to fuse the outputs of the two modules according to their corresponding weights,restoring high-quality images.The experimental results show that the proposed sand and dust image enhancement algorithm eliminates color cast in the image and achieves good results in both subjective and objective evaluations.关键词
图像去沙尘/深度学习/HSV颜色空间/注意力机制/扩张残差卷积模块Key words
image desanding/deep learning/HSV color space/attention mechanism/expansion residual convolution module分类
计算机与自动化引用本文复制引用
侯丁博,陈平..基于多尺度信息与HSV空间的图像去沙尘算法[J].测试技术学报,2025,39(3):305-312,8.基金项目
国家重点研发计划(2023YFE0205800) （2023YFE0205800）
国家自然科学联合基金资助项目(U23A20285) （U23A20285）
山西省重点研发计划(202302150401011):国家自然科学基金面上项目(62471442) （202302150401011）
中央引导地方科技发展项目(YDZJSX2024D037) （YDZJSX2024D037）
国家自然科学基金-青年基金资助项目(62301507) （62301507）
山西省基础研究计划(自由探索类)资助项目(202303021222094) （自由探索类）
