Multisensor Remote Sensing Imagery Super-Resolution with Conditional GAN
Despite the promising performance on benchmark datasets that deep convolutional neural networks have exhibited in single image super-resolution (SISR), there are two underlying limitations to existing methods. First, current supervised learning-based SISR methods for remote sensing satellite imagery...
Main Authors: | Junwei Wang, Kun Gao, Zhenzhou Zhang, Chong Ni, Zibo Hu, Dayu Chen, Qiong Wu |
---|---|
Format: | Article |
Language: | English |
Published: |
American Association for the Advancement of Science (AAAS)
2021-01-01
|
Series: | Journal of Remote Sensing |
Online Access: | http://dx.doi.org/10.34133/2021/9829706 |
Similar Items
-
Enlighten-GAN for Super Resolution Reconstruction in Mid-Resolution Remote Sensing Images
by: Yuanfu Gong, et al.
Published: (2021-03-01) -
Deep Distillation Recursive Network for Remote Sensing Imagery Super-Resolution
by: Kui Jiang, et al.
Published: (2018-10-01) -
Resolution Enhancement of Multispectral Remote Sensing Imagery by Modified Super-Resolution Reconstruction and Blind Deconvolution
by: Chia-Wei Hsu, et al.
Published: (2006) -
Multisensor remote sensing data integration
by: Nedim Kulo
Published: (2019-12-01) -
Multisensor Microwave Remote Sensing in the Cryosphere
by: Remund, Quinn P.
Published: (2003)