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International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

TH1.O-14.5

Hyperspectral and multispectral image fusion: from model-driven to data-driven

Yongqiang Zhao, Haofang Yan, Northwestern Polytechnical University, China; Sha Liu, Shanghai Institute of Aerospace Technology, China
Session:
Multi-resolution and Multimodal Remote Sensing Image Processing and Interpretation
Track:
Invited Sessions
Presentation Time:
Thu, 15 Jul, 09:30-09:45 (UTC)
Thu, 15 Jul, 11:30-11:45 Central Europe Summer Time (UTC +2)
Thu, 15 Jul, 17:30-17:45 China Standard Time (UTC +8)
Thu, 15 Jul, 05:30-05:45 Eastern Daylight Time (UTC -4)
Session Chair:
Gemine Vivone, National Research Council - Institute of Methodologies for Environmental Analysis (CNR - IMAA)
Session Managers:
Adebowale Adebayo and Yang Xu
Presentation
Discussion
Resources
Session TH1.O-14
TH1.O-14.1: An Overview of Multimodal Remote Sensing Data Fusion: From Image to Feature, From Shallow to Deep
Danfeng Hong, German Aerospace Center (DLR), Germany; Jocelyn Chanussot, Université Grenoble Alpes, INRIA, CNRS, Grenoble INP, LJK, France; Xiao Xiang Zhu, German Aerospace Center (DLR); Technical University of Munich (TUM), Germany
TH1.O-14.3: A Fast and Robust Matching System for Multimodal Remote Sensing Image Registration
Yuanxin Ye, Bai Zhu, Liang Zhou, Bruzzone Lorenzo, Southwest Jiaotong University, China
TH1.O-14.4: A DEEP LEARNING-BASED HETEROGENEOUS SPATIO-TEMPORAL-SPECTRAL FUSION: SAR AND OPTICAL IMAGES
Menghui Jiang, School of Resource and Environmental Sciences, Wuhan University, China; Jie Li, School of Geodesy and Geomatics, Wuhan University, China; Huanfeng Shen, School of Remote Sensing and Information Engineering, Wuhan University, China
TH1.O-14.5: Hyperspectral and multispectral image fusion: from model-driven to data-driven
Yongqiang Zhao, Haofang Yan, Northwestern Polytechnical University, China; Sha Liu, Shanghai Institute of Aerospace Technology, China
TH1.O-14.6: A FULL-RESOLUTION TRAINING FRAMEWORK FOR SENTINEL-2 IMAGE FUSION
Matteo Ciotola, Mario Ragosta, Giovanni Poggi, Giuseppe Scarpa, University Federico II, Italy

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