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
PDF ArticleMore Like This
Jun Ke, Ping Wei, and Edmund Y. Lam
SM2F.7 Signal Recovery and Synthesis (SRS) 2014
Elkin Díaz, Jonathan Monsalve, Andrés Guerrero, and Henry Arguello
CTu5D.1 Computational Optical Sensing and Imaging (COSI) 2018
Binlin Wu, M. Alrubaiee, W. Cai, M. Xu, and S. K. Gayen
JTuC10 Computational Optical Sensing and Imaging (COSI) 2009