A Dual-Strategy Learning Framework for Hyperspectral Image Super-Resolution
Hyperspectral image super-resolution (HSI SR) has achieved remarkable success with deep neural networks. Currently, most methods in HSI SR assume a predetermined degradation model during training to synthesize low-resolution images. These methods falter when confronted with HSI exhibiting degradatio...
Saved in:
| Main Authors: | Shuying Li, Ruichao Sun, San Zhang, Qiang Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10891577/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multiscale Spatial-Spectral CNN-Transformer Network for Hyperspectral Image Super-Resolution
by: Jiayang Zhang, et al.
Published: (2025-01-01) -
Hyperspectral Pansharpening Enhanced With Multi-Image Super-Resolution for PRISMA Data
by: Maciej Ziaja, et al.
Published: (2025-01-01) -
CASSNet: Cross-Attention Enhanced Spectral–Spatial Interaction Network for Hyperspectral Image Super-Resolution
by: Zhanxu Zhang, et al.
Published: (2025-01-01) -
M<inline-formula><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula>Convformer: Multiscale Masked Hybrid Convolution-Transformer Network for Hyperspectral Image Super-Resolution
by: Shuo Wang, et al.
Published: (2025-01-01) -
Unsupervised Spectral Super-Resolution Guided by Spectral Sampling Priors
by: Xintao Zhong, et al.
Published: (2025-01-01)