SSSMN: Spatial-spectral sparse Mamba network for efficient hyperspectral fusion super-resolution
- 14 March 2026
- journal article
- Published by Elsevier in Pattern Recognition
- Vol. 178
Abstract
No abstract availableFunding Information
- National Natural Science Foundation of China (12072366)
- National Natural Science Foundation of China (62221002)
- National Natural Science Foundation of China (62422108)
- National Natural Science Foundation of China (62201205)
- National University's Basic Research Foundation of China
- Fundamental Research Funds for the Central Universities (531118010744)
- Natural Science Foundation of Fujian Province (2024J01227)
This publication has 27 references indexed in Scilit:
- Cross-domain-aware deep unfolding transformer for hyperspectral image super-resolutionPattern Recognition, 2025
- CMANet: A CNN-Mamba aggregation network for face super-resolutionPattern Recognition, 2025
- Spatial–spectral unfolding network with mutual guidance for multispectral and hyperspectral image fusionPattern Recognition, 2024
- Pan-Mamba: Effective pan-sharpening with state space modelInformation Fusion, 2024
- Spatial–Spectral Interaction Super-Resolution CNN–Mamba Network for Fusion of Satellite Hyperspectral and Multispectral ImageIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024
- Deep blind super-resolution for hyperspectral imagesPattern Recognition, 2024
- Low-Rank Transformer for High-Resolution Hyperspectral Computational ImagingInternational Journal of Computer Vision, 2024
- Learning spatial-spectral dual adaptive graph embedding for multispectral and hyperspectral image fusionPattern Recognition, 2024
- Multiscale spatial–spectral transformer network for hyperspectral and multispectral image fusionInformation Fusion, 2023
- Hyperspectral super-resolution via coupled tensor ring factorizationPattern Recognition, 2022