HUD generates hyperspectral images by running a diffusion process on unmixed abundance maps, then decoding with the endmember matrix, achieving high point fidelity but only average block diversity in the paper's own experiments.
Spectral Super-Resolution Meets Deep Learning: Achievements and Challenges,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
Hyperspectral Image Generation with Unmixing Guided Diffusion Model
HUD generates hyperspectral images by running a diffusion process on unmixed abundance maps, then decoding with the endmember matrix, achieving high point fidelity but only average block diversity in the paper's own experiments.