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Conference papers

Travelling salesman-based variable density sampling

Nicolas Chauffert 1, * Philippe Ciuciu 1 Jonas Kahn 2 Pierre Weiss 3
* Corresponding author
1 PARIETAL - Modelling brain structure, function and variability based on high-field MRI data
Inria Saclay - Ile de France, NEUROSPIN - Service NEUROSPIN
IMT - Institut de Mathématiques de Toulouse UMR5219, ITAV - Institut des Technologies Avancées en sciences du Vivant
Abstract : Compressed sensing theory indicates that selecting a few measurements independently at random is a near optimal strategy to sense sparse or compressible signals. This is infeasible in practice for many acquisition devices that acquire sam- ples along continuous trajectories. Examples include magnetic resonance imaging (MRI), radio-interferometry, mobile-robot sampling, ... In this paper, we propose to generate continuous sampling trajectories by drawing a small set of measurements independently and joining them using a travelling salesman problem solver. Our contribution lies in the theoretical derivation of the appropriate probability density of the initial drawings. Preliminary simulation results show that this strategy is as efficient as independent drawings while being implementable on real acquisition systems.
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Submitted on : Thursday, July 25, 2013 - 6:01:48 PM
Last modification on : Tuesday, January 25, 2022 - 3:12:01 AM
Long-term archiving on: : Saturday, October 26, 2013 - 4:27:48 AM


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  • HAL Id : hal-00848290, version 1
  • ARXIV : 1307.6837


Nicolas Chauffert, Philippe Ciuciu, Jonas Kahn, Pierre Weiss. Travelling salesman-based variable density sampling. SampTA - 10th Conference International Conference on Sampling Theory and Applications, Jul 2013, Bremen, Germany. pp.509-512. ⟨hal-00848290⟩



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