• DOI:10.1109/TIT.2006.871582
Corpus ID: 206737254

Compressed sensing

@article{Donoho2006CompressedS,
  title={Compressed sensing},
  author={D. Donoho},
  journal={IEEE Transactions on Information Theory},
  year={2006},
  volume={52},
  pages={1289-1306}
}

D. Donoho

Published 2006

Computer Science

IEEE Transactions on Information Theory

Suppose x is an unknown vector in Ropfm (a digital image or signal); we plan to measure n general linear functionals of x and then reconstruct. If x is known to be compressible by transform coding with a known transform, and we reconstruct via the nonlinear procedure defined here, the number of measurements n can be dramatically smaller than the size m. Thus, certain natural classes of images with m pixels need only n=O(m1/4log5/2(m)) nonadaptive nonpixel samples for faithful recovery, as… CONTINUE READING

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