M<inline-formula><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula>Convformer: Multiscale Masked Hybrid Convolution-Transformer Network for Hyperspectral Image Super-Resolution

M<inline-formula><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula>Convformer: Multiscale Masked Hybrid Convolution-Transformer Network for Hyperspectral Image Super-Resolution

How to fully utilize spectral correlation to improve spatial resolution is the focus of current hyperspectral image super-resolution (HSI-SR) research. Existing approaches either combine deep models with various advanced attention mechanisms to form an end-to-end framework, or concentrate on the pro...

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Bibliographic Details
Main Authors: Shuo Wang, Boneng Shi, Ninglian Wang, Yuzhu Zhang, Yan Zhu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Hyperspectral image (HSI)
masking strategy
multiscale learning
super-resolution
Online Access:https://ieeexplore.ieee.org/document/11002489/
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