Pan-Denoising: Guided Hyperspectral Image Denoising via Weighted Represent Coefficient Total Variation-Reference-Cited by-同舟云学术

Pan-Denoising: Guided Hyperspectral Image Denoising via Weighted Represent Coefficient Total Variation

Published:2024 Issue: Volume:62 Page:1-14
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Xu Shuang¹^ORCID,Ke Qiao¹^ORCID,Peng Jiangjun¹^ORCID,Cao Xiangyong²^ORCID,Zhao Zixiang³

Affiliation:

1. School of Mathematics and Statistics, Northwestern Polytechnical University, Xi’an, China

2. School of Electronic and Information Engineering and the Key Laboratory of Intelligent Networks and Network Security, Ministry of Education, Xi’an Jiaotong University, Xi’an, China

3. School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, China

Funder

China NSFC Projects

Guangdong Basic and Applied Basic Research Foundation

Shaanxi Fundamental Science Research Project for Mathematics and Physics

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/36/10354519/10663706.pdf?arnumber=10663706

Reference74 articles.

1. Hyperspectral Image Classification With Markov Random Fields and a Convolutional Neural Network

2. A Multilevel Spatial and Spectral Feature Extraction Network for Marine Oil Spill Monitoring Using Airborne Hyperspectral Image

3. Medical hyperspectral image classification based weakly supervised single-image global learning network

4. Hyperspectral Denoising Using Asymmetric Noise Modeling Deep Image Prior

5. Hyperspectral Compressive Snapshot Reconstruction via Coupled Low-Rank Subspace Representation and Self-Supervised Deep Network