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Compressive sensing matrix design using principal components analysis

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Abstract

This paper introduces a matrix formulation in the compressive spectral imaging sensing problem which reduces computational complexity and allows to design sensing matrices using principal components analysis, leading to improved reconstructions.

© 2017 Optical Society of America

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