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Compressive Sensing in Acoustic Imaging

  • Nancy Bertin
  • Laurent Daudet
  • Valentin Emiya
  • Rémi Gribonval
Part of the Applied and Numerical Harmonic Analysis book series (ANHA)

Abstract

Acoustic sensing is at the heart of many applications, ranging from underwater sonar and nondestructive testing to the analysis of noise and their sources, medical imaging, and musical recording. This chapter discusses a palette of acoustic imaging scenarios where sparse regularization can be leveraged to design compressive acoustic imaging techniques. Nearfield acoustic holography (NAH) serves as a guideline to describe the general approach. By coupling the physics of vibrations and that of wave propagation in the air, NAH can be expressed as an inverse problem with a sparsity prior and addressed through sparse regularization. In turn, this can be coupled with ideas from compressive sensing to design semi-random microphone antennas, leading to improved hardware simplicity, but also to new challenges in terms of sensitivity to a precise calibration of the hardware and software scalability. Beyond NAH, this chapter shows how compressive sensing is being applied to other acoustic scenarios such as active sonar, sampling of the plenacoustic function, medical ultrasound imaging, localization of directive sources, and interpolation of plate vibration response.

Keywords

Impulse Response Acoustic Field Tikhonov Regularization Acoustic Imaging Sparse Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors wish to warmly thank François Ollivier, Jacques Marchal, and Srdjan Kitic for the figures, as well as Gilles Chardon, Rmi Mignot, Antoine Peillot, and the colleagues from the ECHANGE and PLEASE project whose contributions have been essential in the work described in this chapter. This work was supported in part by French National Research, ECHANGE project (ANR-08-EMER-006 ECHANGE) and by the European Research Council, PLEASE project (ERC-StG-2011-277906).

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Nancy Bertin
    • 1
  • Laurent Daudet
    • 2
  • Valentin Emiya
    • 3
  • Rémi Gribonval
    • 4
  1. 1.IRISA - CNRS UMR 6074, PANAMA team (Inria & CNRS)Rennes CedexFrance
  2. 2.Paris Diderot University, Institut Langevin, ESPCI ParisTech, CNRS UMR 7587ParisFrance
  3. 3.Aix-Marseille Université, CNRS, LIF UMR 7279Marseille Cedex 9France
  4. 4.Inria, PANAMA team (Inria & CNRS)Rennes CedexFrance

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