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International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

TU2.MM-15.5

INCREASING LANDSAT 5 TM SPATIAL RESOLUTION TO 15 M USING A SUPER-RESOLUTION DEEP LEARNING MODEL TRAINED WITH PAN-SHARPENED LANDSAT 7 ETM+ DATA

Fabien H. Wagner, Foundation for Science, Technology and Space Applications-FUNCATE, Brazil; Peter Joyce, Roel Brienen, Emanuel Gloor, University of Leeds, United Kingdom
Session:
Image Restoration and Enhancement
Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)
Presentation Time:
Tue, 13 Jul, 11:20-11:25 (UTC)
Tue, 13 Jul, 13:20-13:25 Central Europe Summer Time (UTC +2)
Tue, 13 Jul, 19:20-19:25 China Standard Time (UTC +8)
Tue, 13 Jul, 07:20-07:25 Eastern Daylight Time (UTC -4)
Session Co-Chairs:
Daniel Cerra, German Aerospace Center (DLR) and Daniel Zanotta, UNISINOS
Session Manager:
Lynette Dias
Presentation
Discussion
Resources
Session TU2.MM-15
TU2.MM-15.1: A LOW-RANK AND SPARSE CONSTRAINED DARK CHANNEL PRIOR FOR CLOUD REMOVAL IN REMOTE SENSING IMAGE SEQUENCE
Jin Cheng, Ye Zhang, Xinyu Zhou, Shaoqi Shi, Harbin Institute of Technology, China
TU2.MM-15.2: A RECURRENT REFINEMENT NETWORK FOR SATELLITE VIDEO SUPER-RESOLUTION
Yi Xiao, Xin Su, Qiangqiang Yuan, Wuhan University, China
TU2.MM-15.3: A MULTI-LOOKING APPROACH FOR SPATIAL SUPER-RESOLUTION ON LABORATORY-BASED HYPERSPECTRAL IMAGE
Daniel Zanotta, Ademir Marques Jr., Alysson Soares Aires, Fabiane Bordin, Graciela Racolte, João Gabriel Motta, Lucas Kupssinsku, Marianne Muller, Rafael Kenji Horota, Tainá Thomassim Guimarães, Vinícius Sales, Unisinos University, Brazil; Caroline Cazarin, Cenpes, Brazil; Luiz Gonzaga Jr, Maurício Roberto Veronez, Unisinos University, Brazil
TU2.MM-15.4: SPATIAL-SPECTRAL TOTAL VARIATION CONSTRAINED COLLABORATIVE TENSOR REGULARIZATION FOR DUAL-CAMERA COMPRESSIVE HYPERSPECTRAL IMAGING
Zhenghui Liang, Yang Xu, Liang Xiao, Zhihui Wei, Nanjing University of Science and Technology, China
TU2.MM-15.5: INCREASING LANDSAT 5 TM SPATIAL RESOLUTION TO 15 M USING A SUPER-RESOLUTION DEEP LEARNING MODEL TRAINED WITH PAN-SHARPENED LANDSAT 7 ETM+ DATA
Fabien H. Wagner, Foundation for Science, Technology and Space Applications-FUNCATE, Brazil; Peter Joyce, Roel Brienen, Emanuel Gloor, University of Leeds, United Kingdom
TU2.MM-15.6: PROBA-V-REF: REPURPOSING THE PROBA-V CHALLENGE FOR REFERENCE-AWARE SUPER RESOLUTION
Ngoc-Long Nguyen, Jérémy Anger, Axel Davy, Pablo Arias, Gabriele Facciolo, Université Paris-Saclay, France
TU2.MM-15.7: DEEP LEARNING FOR MULTIPLE-IMAGE SUPER-RESOLUTION OF SENTINEL-2 DATA
Michal Kawulok, Tomasz Tarasiewicz, Jakub Nalepa, Diana Tyrna, Daniel Kostrzewa, KP Labs / Silesian University of Technology, Poland
TU2.MM-15.8: Improved Image Aggregation for Large-Scale Cloud-Free Image Creation
David Nagy, Zhenya Warshavsky, Lloyd Hughes, Project Canopy, United States
TU2.MM-15.9: COMPRESSED IMAGING IN FOREIGN OBJECT DEBRIS RADAR
Fei Qin, Xingdong Liang, Xiangxi Bu, Zhiyuan Zeng, Aerospace Information Reasearch Institute, Chinese Academy of Sciences, China
TU2.MM-15.10: HYPERSPECTRAL IMAGERY SUPER-RESOLUTION BASED ON SELF-CALIBRATED ATTENTION RESIDUAL NETWORK
Baorui Wang, Shaohui Mei, Yan Feng, Northwestern Polytechnical University, China; Qian Du, Mississippi State University, Armenia

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