AI RESEARCH
Spectral Dynamic Attention Network for Hyperspectral Image Super-Resolution
arXiv CS.CV
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ArXi:2604.27326v1 Announce Type: cross Hyperspectral image super-resolution is essential for enhancing the spatial fidelity of HSI data, yet existing deep learning methods often struggle with substantial spectral redundancy and the limited non-linear modeling capacity of standard feed-forward networks (FFNs). To address these challenges, we propose Spectral Dynamic Attention Network (SDANet), a framework designed to adaptively suppress redundant spectral interactions.