Abstract
Compressive sensing enables the efficient acquisition of hyperspectral images cubes. The Code Aperture Spectral Imaging (CASSI) system is one such architecture based on a single snap shot. This paper shows the mathematical framework for a new architecture, the Code Aperture Agile Spectral Imaging (CAASI), which extends the capabilities of the CASSI to allow multiple measurements. An optimization algorithm based on a new mathematical framework finds optimal code apertures. Given a set of desired spectral bands, the CAASI has the capability to generate a set of measurements with only the information of interest. Several simulations are shown to illustrated the advantage and capabilities of the optimized code apertures.
© 2011 Optical Society of America
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