南昌工程学院学报2024，Vol.43Issue(3)：88-96,9.
基于深度学习的高光谱图像去噪综述
A review of hyperspectral image denoising based on deep learning
摘要
Abstract
Hyperspectral images are widely used in agriculture,earth science,geological disasters and other fields because hyperspectral images have the advantage that image integrates with spectrum.However,in the imaging process of hyperspec-tral image,due to various factors,hyperspectral images will inevitably be polluted by multiple noises.The existence of noises often limits the application value of hyperspectral images.Therefore,hyperspectral image denoising is an important way of image preprocessing.As one of the rapidly developing technologies in recent years,deep learning has been successfully ap-plied in the task of hyperspectral image denoising.The number of research results on deep learning-based hyperspectral im-age denoising is increasing year by year.In order to facilitate a more systematic and comprehensive exploration of this field,this paper outlines the research progress of deep learning-based hyperspectral image denoising,classifies and summarizes the existing main research findings.Finally,the future research trends in this field are prospected.关键词
高光谱图像去噪/深度学习/卷积神经网络/循环神经网络/注意力机制Key words
hyperspectral image denoising/deep learning/convolution neural network/recurrent neural network/attention mechanism分类
计算机与自动化引用本文复制引用
张俊,谭耀鑫,卢静静,徐晨光,邓承志..基于深度学习的高光谱图像去噪综述[J].南昌工程学院学报,2024,43(3):88-96,9.基金项目
江西省自然科学基金资助项目(20232BAB201017) （20232BAB201017）
南昌工程学院研究生创新计划项目(YJSCX202316) （YJSCX202316）
