Dictionary based Hyperspectral Image Reconstruction Captured with CS-MUSI

The Compressive Sensing Miniature Ultra-Spectral Imaging (CS-MUSI) camera uses a spectral modulator and a grayscale sensor in order to capture an encoded compressed spectral signal. Using the compressive sensing (CS) theory hyperspectral (HS) cubes with hundreds of spectral bands can be reconstructed from an order of magnitude fewer samples. In this work, we show that by using spectral dictionary, as the sparsifying operator, for reconstruction of CS HS images acquired with our CS-MUSI camera, we can both increase the reconstruction quality and reduce the number of measurements CS theory requires as well.