WE1.R3.1: IMPROVED REGRESSION-BASED COMPONENT-SUBSTITUTION PANSHARPENING OF WORLDVIEW-2/3 DATA THROUGH AUTOMATIC REALIGNMENT OF SPECTROMETERS
Alberto Arienzo, Luciano Alparone, University of Florence, Italy; Andrea Garzelli, University of Siena, Italy
WE1.R3.2: A NOVEL FIDELITY BASED ON THE ADAPTIVE DOMAIN FOR PANSHARPENING
Jin-Liang Xiao, Ting-Zhu Huang, Liang-Jian Deng, Ting Xu, University of Electronic Science and Technology of China, China
WE1.R3.3: BALANCING SPECTRAL AND SPATIAL QUALITY IN CNN-BASED UNSUPERVISED PANSHARPENING
Matteo Ciotola, Giuseppe Guarino, Giovanni Poggi, University Federico II, Italy; Giuseppe Scarpa, University Parthenope, Italy
WE1.R3.5: DEGRADATION-AWARE SELF-SUPERVISED MULTI-TEMPORAL SUPER-RESOLUTION
Matteo Impieri, Diego Valsesia, Tiziano Bianchi, Enrico Magli, Politecnico di Torino, Italy
WE1.R3.6: Diffusion models with Cross-Modal data for Super-resolution of Sentinel-2 to 2.5 meter Resolution
Muhammad Sarmad, Norsk Regnesentral, Norway; Michael Kampffmeyer, UiT The Arctic University of Norway, Norwegian Computing Center, Norway; Arnt B. Salberg, Norsk Regnesentral, Norway
WE1.R3.7: Multi-image fusion for super-resolving individual Sentinel-2 images
Bartlomiej Pogodzinski, Silesian University of Technology / Saarland University, Poland; Tomasz Tarasiewicz, Silesian University of Technology, Poland; Michal Kawulok, Silesian University of Technology / KP Labs, Poland
