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Compressive Sensing in Acoustic Imaging

Nancy Bertin 1 Laurent Daudet 2 Valentin Emiya 3 Rémi Gribonval 1
1 PANAMA - Parcimonie et Nouveaux Algorithmes pour le Signal et la Modélisation Audio
3 QARMA - éQuipe AppRentissage et MultimediA [Marseille]
LIF - Laboratoire d'informatique Fondamentale de Marseille
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 compressed sensing is being applied to other acoustic scenarios such as active sonar, sampling of plenacoustic function, medical ultrasound imaging, localization of directive sources and interpolation of plate vibration response.
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Contributor : Nancy Bertin <>
Submitted on : Tuesday, July 28, 2015 - 2:33:28 PM
Last modification on : Tuesday, December 8, 2020 - 9:52:48 AM


  • HAL Id : hal-01180899, version 1


Nancy Bertin, Laurent Daudet, Valentin Emiya, Rémi Gribonval. Compressive Sensing in Acoustic Imaging. Holger Boche; Robert Calderbank; Gitta Kutyniok; Jan Vybíral. Compressed Sensing and its Applications - MATHEON Workshop 2013, Birkhäuser Basel, pp.169-192, 2015, Applied and Numerical Harmonic Analysis, 978-3-319-16041-2. ⟨hal-01180899⟩



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