@article{d7ef22525e44439d9db407a0a62fe8eb,
title = "Compressed sampling strategies for tomography",
author = "Yan Kaganovsky and Daheng Li and Andrew Holmgren and HyungJu Jeon and MacCabe, \{Kenneth P.\} and Politte, \{David G.\} and Joseph O'Sullivan and Lawrence Carin and Brady, \{David J.\}",
note = "We investigate new sampling strategies for projection tomography, enabling one to employ fewer measurements than expected from classical sampling theory without significant loss of information. Inspired by compressed sensing, our approach is based on the understanding that many real objects are compressible in some known representation, implying that the number of degrees of freedom defining an object is often much smaller than the number of pixels/voxels.",
year = "2014",
month = jun,
day = "9",
doi = "10.1364/JOSAA.31.001369",
language = "American English",
volume = "31",
journal = "Journal of the Optical Society of America A",
}