AI RESEARCH
A Latent Representation Learning Framework for Hyperspectral Image Emulation in Remote Sensing
arXiv CS.LG
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ArXi:2603.21911v1 Announce Type: cross Synthetic hyperspectral image (HSI) generation is essential for large-scale simulation, algorithm development, and mission design, yet traditional radiative transfer models remain computationally expensive and often limited to spectrum-level outputs. In this work, we propose a latent representation-based framework for hyperspectral emulation that learns a latent generative representation of hyperspectral data.