A Compressive Sensing Snapshot Imaging Spectrometer (CSSIS) and its performance are described. The numberof spectral bins recorded in a traditional tiled array spectrometer is limited to the number of filters. By properlydesigning the filters and leveraging compressive sensing techniques, more spectral bins can be reconstructed. Sim-ulation results indicate that closely-spaced spectral sources that are not resolved with a traditional spectrometercan be resolved with the CSSIS. The nature of the filters used in the CSSIS enable higher signal-to-noise ratiosin measured signals. The filters are spectrally broad relative to narrow-line filters used in traditional systems,and hence more light reaches the imaging sensor. This enables the CSSIS to outperform a traditional systemin a classification task in the presence of noise. Simulation results on classifying in the compressive domain areshown. This obviates the need for the computationally-intensive spectral reconstruction algorithm.
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