A Note on Compressed Sensing of Structured Sparse Wavelet Coefficients From Subsampled Fourier Measurements

B. Adcock; A. Hansen; B. Roman

DOI:10.1109/LSP.2016.2550101

Corpus ID: 14129655

A Note on Compressed Sensing of Structured Sparse Wavelet Coefficients From Subsampled Fourier Measurements

@article{Adcock2016ANO,
  title={A Note on Compressed Sensing of Structured Sparse Wavelet Coefficients From Subsampled Fourier Measurements},
  author={B. Adcock and A. Hansen and B. Roman},
  journal={IEEE Signal Processing Letters},
  year={2016},
  volume={23},
  pages={732-736}
}

B. Adcock, A. Hansen, B. Roman

Published 2016

Mathematics, Computer Science

IEEE Signal Processing Letters

We consider signal recovery from Fourier measurements using compressed sensing (CS) with wavelets. For discrete signals with structured sparse Haar wavelet coefficients, we give the first proof of near-optimal recovery from discrete Fourier samples taken according to an appropriate variable density sampling scheme. Crucially, in taking into account such structured sparsity-known as sparsity in levels-as opposed to just sparsity, this result yields recovery guarantees that agree with the… CONTINUE READING

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