SpectraMorph is a physics-guided self-supervised framework for hyperspectral super-resolution that enforces an unmixing bottleneck to extract endmembers from low-resolution HSI and predict abundance-like maps from MSI for linear mixing reconstruction.
MIMO-SST: Multi-input multi-output spatial- spectral transformer for hyperspectral and multispectral image fusion
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2025 2verdicts
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A self-supervised per-pixel MLP that learns spectral inversion from synthetic LR-MSI created via SRF applied to LR-HSI and then applies the mapping to HR-MSI to estimate HR-HSI.
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SpectraMorph: Structured Latent Learning for Self-Supervised Hyperspectral Super-Resolution
SpectraMorph is a physics-guided self-supervised framework for hyperspectral super-resolution that enforces an unmixing bottleneck to extract endmembers from low-resolution HSI and predict abundance-like maps from MSI for linear mixing reconstruction.
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SpectraLift: Physics-Guided Spectral-Inversion Network for Self-Supervised Hyperspectral Image Super-Resolution
A self-supervised per-pixel MLP that learns spectral inversion from synthetic LR-MSI created via SRF applied to LR-HSI and then applies the mapping to HR-MSI to estimate HR-HSI.