MHealth hyperspectral learning for instantaneous spatiospectral imaging of hemodynamics.

ABSTRACT: Hyperspectral imaging acquires data in both the spatial and frequency domains to offer abundant physical or biological information. However, conventional hyperspectral imaging has intrinsic limitations of bulky instruments, slow data acquisition rate, and spatiospectral trade-off. Here we introduce hyperspectral learning for snapshot hyperspectral imaging in which sampled hyperspectral data in a small subarea are incorporated into a learning algorithm to recover the hypercube. Hyperspectral learning exploits the idea that a photograph is more than merely a picture and contains detailed spectral information. A small sampling of hyperspectral data enables spectrally informed learning to recover a hypercube from a red-green-blue (RGB) image without complete hyperspectral measurements. Hypersp

SUBMITTER: Ji Y 

PROVIDER: S-EPMC10129064 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature