Compressive Hyperspectral Imaging With Side Information

Xin Yuan, Tsung-Han Tsai, Ruoyu Zhu, Patrick Llull, David Brady, Lawrence Carin
2015 IEEE Journal on Selected Topics in Signal Processing  
A blind compressive sensing algorithm is proposed to reconstruct hyperspectral images from spectrally-compressed measurements.The wavelength-dependent data are coded and then superposed, mapping the three-dimensional hyperspectral datacube to a two-dimensional image. The inversion algorithm learns a dictionary in situ from the measurements via global-local shrinkage priors. By using RGB images as side information of the compressive sensing system, the proposed approach is extended to learn a
more » ... pled dictionary from the joint dataset of the compressed measurements and the corresponding RGB images, to improve reconstruction quality. A prototype camera is built using a liquid-crystal-on-silicon modulator. Experimental reconstructions of hyperspectral datacubes from both simulated and real compressed measurements demonstrate the efficacy of the proposed inversion algorithm, the feasibility of the camera and the benefit of side information.
doi:10.1109/jstsp.2015.2411575 fatcat:v54lrrop5nhshlcyrzdaltjua4