Slide Fifth
Slide Second
Slide Fourth
Slide Sixth
Slide Sixth
International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

WE2.MM-5.8

NON-LOCAL MEANS LOW-RANK APPROXIMATION FOR HYPERSPECTRAL DENOISING

Bin Zhao, Jóhannes Rúnar Sveinsson, Magnus O. Ulfarsson, University of Iceland, Iceland; Jocelyn Chanussot, Université Grenoble Alpes; University of Iceland, Iceland
Session:
Advances in Image Denoising and Restoration
Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)
Presentation Time:
Wed, 14 Jul, 11:35-11:40 (UTC)
Wed, 14 Jul, 13:35-13:40 Central Europe Summer Time (UTC +2)
Wed, 14 Jul, 19:35-19:40 China Standard Time (UTC +8)
Wed, 14 Jul, 07:35-07:40 Eastern Daylight Time (UTC -4)
Session Co-Chairs:
Mauro Dalla Mura, Grenoble Institute of Technology and BIN ZHAO, UNIVERSITY OF ICELAND
Session Managers:
Frederik Priem and Arvind Gauns
Presentation
Discussion
Resources
Session WE2.MM-5
WE2.MM-5.1: HYPERSPECTRAL DENOISING VIA GLOBAL TENSOR RING DECOMPOSITION AND LOCAL UNSUPERVISED DEEP IMAGE PRIOR
Jian-Li Wang, Ting-Zhu Huang, Xi-Le Zhao, School of Mathematical Sciences, University of Electronic Science and Technology of China, China; Teng-Yu Ji, School of Mathematics and Statistics, Northwestern Polytechnical University, China; Tai-Xiang Jiang, School of Economic Information Engineering, Southwestern University of Finance and Economics, China
WE2.MM-5.2: A NEW DEEP HIERARCHY FOR UNDERWATER IMAGE RECONSTRUCTION
Yafei Song, Ganggang Dong, Xidian University, China
WE2.MM-5.3: CLOUD REMOVAL FOR SINGLE VISIBLE IMAGE BASED ON MODIFIED DARK CHANNEL PRIOR WITH MULTIPLE SCALE
Shaoqi Shi, Ye Zhang, Xinyu Zhou, Jin Cheng, Harbin Institute of Technology, China
WE2.MM-5.4: LEARNING A MODEL-BASED DEEP HYPERSPECTRAL DENOISER FROM A SINGLE NOISY HYPERSPECTRAL IMAGE
Guanyiman Fu, Fengchao Xiong, Shuyin Tao, Jianfeng Lu, Nanjing University of Science and Technology, China; Jun Zhou, Griffith University, Australia; Yuntao Qian, Zhejiang University, China
WE2.MM-5.5: Hyperspectral Image Super-Resolution via Multi-Domain Feature Learning
Qiang Li, Qi Wang, Xuelong Li, Northwestern Polytechnical University, China
WE2.MM-5.6: HYPERSPECTRAL IMAGE DENOISING WITH COLLABORATIVE TOTAL VARIATION AND LOW RANK REGULARIZATION
Lu Yang, Jinhuan Xu, Liang Xiao, Nanjing University of Science and Technology, China
WE2.MM-5.7: A PROPOSED FULLY CONSTRAINED LEAST SQUARES FOR SOLVING SPARSE ENDMEMBER FRACTIONS WITH LINEAR SPECTRAL MIXTURE MODEL
Cuicui Ji, Chongqing Jiaotong University, China; Xiaosong Li, Aerospace Information Reasearch Institute, Chinese Academy of Sciences, China; Jinying Wang, Piesat Information Technology Co., Ltd., China; Maolin Chen, Jianping Pan, Chongqing Jiaotong University, China
WE2.MM-5.8: NON-LOCAL MEANS LOW-RANK APPROXIMATION FOR HYPERSPECTRAL DENOISING
Bin Zhao, Jóhannes Rúnar Sveinsson, Magnus O. Ulfarsson, University of Iceland, Iceland; Jocelyn Chanussot, Université Grenoble Alpes; University of Iceland, Iceland

Quicklinks

Downloads

Programme guide