TH2.M3.4
TOWARDS DEEP LINE-BASED ARCHITECTURES FOR ONBOARD HYPERSPECTRAL IMAGE SUPER-RESOLUTION
Davide Piccinini, Diego Valsesia, Enrico Magli, Politecnico di Torino, Italy
Session:
TH2.M3: Advancements in Super-Resolution Techniques for Remote Sensing Image Enhancement Oral
Track:
AI and Big Data
Location:
Mezzanine: Room M3
Presentation Time:
Thursday, 7 August, 11:15 - 11:30
Session Co-Chairs:
Royston Rodrigues, NEC and Cindy Ong, Commonwealth Scientific and Industrial Research Organisation
Session TH2.M3
TH2.M3.1: REAL-WORLD SUPER-RESOLUTION: HOW TO OVERCOME RECONSTRUCTION ARTIFACTS?
Bartosz Ciucka, Tomasz Tarasiewicz, Michal Kawulok, Silesian University of Technology, Poland
TH2.M3.2: SINGLE SATELLITE IMAGE SUPER-RESOLUTION UP TO X8
Liuyun Duan, Michael Swaine, Nicolas Girard, Sebastien Tripodi, Sacha Lepretre, LuxCarta, France
TH2.M3.3: ENHANCING HYPERSPECTRAL IMAGE SYNTHESIS VIA THE SPECTRAL SUPER-RESOLUTION POST-PROCESSING NETWORK
Damla Akcaoglu, Erkut Erdem, Seniha Esen Yuksel, Hacettepe University, Turkey; Aykut Erdem, Koç University, Turkey
TH2.M3.4: TOWARDS DEEP LINE-BASED ARCHITECTURES FOR ONBOARD HYPERSPECTRAL IMAGE SUPER-RESOLUTION
Davide Piccinini, Diego Valsesia, Enrico Magli, Politecnico di Torino, Italy
TH2.M3.5: A DUAL-BRANCH GLOBAL-LOCAL FEATURE LEARNING NETWORK BY INTEGRATING CNN AND TRANSFORMER FOR REMOTE SENSING IMAGE SUPER-RESOLUTION
Zhijie Zhang, Ruyi Feng, Lizhe Wang, Runyu Fan, China University of Geosciences, China
Resources