17 - 22 July, 2022 • Physical: Kuala Lumpur Convention Centre (KLCC), Kuala Lumpur, Malaysia • Hybrid: Online Platform

Preserving Our Heritage, Enabling Our Future Through Remote Sensing

17 - 22 July, 2022 • Physical: Kuala Lumpur Convention Centre (KLCC), Kuala Lumpur, Malaysia • Hybrid: Online Platform

TU5.V8.5

TWO-STAGE FUSION BASED CNN FOR HYPERSPECTRAL PANSHARPENING

Jinhua Xie, Lin He, School of Automation Science and Engineering, South China University of Technology, China
Session:
Spatial Resolution Enhancement Oral Virtual
Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)
Location:
Virtual Room 8
Presentation Time:
Tue, 19 Jul, 20:50 - 21:05 Malaysia Time (UTC +8)
Tue, 19 Jul, 14:50 - 15:05 Central European Time (UTC +1)
Tue, 19 Jul, 12:50 - 13:05 UTC
Tue, 19 Jul, 08:50 - 09:05 Eastern Time (UTC -5)
Session Co-Chairs:
Gemine Vivone, CNR-IMAA and Mercedes E Paoletti, Complutense University of Madrid
Session Manager:
Wei Pin, Peter Choo
Presentation
Discussion
Resources
No resources available.
Session TU5.V8
TU5.V8.1: MULTISPECTRAL PANSHARPENING BASED ON HIGH-PASS MODULATION REGRESSION
Hongyu Yao, Peng Wang, Xun Shen, Nanjing University of Aeronautics and Astronautics, China; Lixin Shi, Chunlei Zhao, Key Laboratory of Meteorology and Ecological Environment of Hebei Province, China
TU5.V8.2: SD-DSAN: SALIENCY-DRIVEN DENSE SPATIAL ATTENTION NETWORK FOR PAN-SHARPENING
Wanning Zhu, Yang Sun, Shan Wang, Libao Zhang, Beijing Normal University, China
TU5.V8.3: WaveFusion: Wavelet Assistant Fusion Model for Pan-Sharpening
Yinghui Xing, Yan Zhang, Yanning Zhang, Northwestern Polytechnical University, China
TU5.V8.4: THREE-BRANCH MULTILEVEL ATTENTIVE FUSION NETWORK FOR HYPERSPECTRAL PANSHARPENING
Peiyan Guan, Edmund Y. Lam, University of Hong Kong, Hong Kong SAR China
TU5.V8.5: TWO-STAGE FUSION BASED CNN FOR HYPERSPECTRAL PANSHARPENING
Jinhua Xie, Lin He, School of Automation Science and Engineering, South China University of Technology, China
TU5.V8.6: SUPER RESOLUTION APPROACH FOR THE SATELLITE DATA BASED ON THE GENERATIVE ADVERSARIAL NETWORKS
Mykola Lavreniuk, Nataliia Kussul, Andrii Shelestov, Space Research Institute, Ukraine; Alla Lavrenyuk, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine; Leonid Shumilo, Department of Geographical Sciences, University of Maryland, United States