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By leveraging unmixing-informed spectral prompts, USP-Mamba achieves superior hyperspectral image reconstruction while maintaining spatial continuity and contextual integrity.
Synthetic training data can unlock robust homography estimation across diverse image modalities, even when real paired data is scarce.
