Abstract
We present a hybrid camera system that combines optical designs with computational processing to achieve content-adaptive high-resolution hyperspectral video acquisition. In particular, we record two video streams: one high-spatial resolution RGB video and one low-spatial resolution hyperspectral video in which the recorded points are dynamically selected using a spatial light modulator (SLM). Then through video-frame registration and a spatio-temporal spreading of the co-located spectral/RGB information, video with high spatial and spectral resolution is produced. The sampling patterns on the SLM are generated on-the-fly according to the scene content, which fully exploits the self-adaptivity of the hybrid camera system. With an experimental prototype, we demonstrate significantly improved accuracy and efficiency as compared to the state-of-the-art.
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