On variable density compressive sampling

Gilles Puy*, Pierre Vandergheynst, Yves Wiaux

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

72 Citations (Scopus)


Incoherence between sparsity basis and sensing basis is an essential concept for compressive sampling. In this context, we advocate a coherence-driven optimization procedure for variable density sampling. The associated minimization problem is solved by use of convex optimization algorithms. We also propose a refinement of our technique when prior information is available on the signal support in the sparsity basis. The effectiveness of the method is confirmed by numerical experiments. Our results also provide a theoretical underpinning to state-of-the-art variable density Fourier sampling procedures used in MRI.

Original languageEnglish
Article number5976374
Pages (from-to)595-598
Number of pages4
JournalIEEE Signal Processing Letters
Issue number10
Publication statusPublished - Oct 2011


  • Compressed sensing
  • magnetic resonance imaging
  • variable density sampling

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics


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