title: TomoPIV meets Compressed Sensing
creator: Petra, Stefania
creator: Schnörr, Christoph
subject: ddc-510
subject: 510 Mathematics
description: We study the discrete tomography problem in Experimental Fluid Dynamics - Tomographic Particle Image Velocimetry (TomoPIV) - from the viewpoint of compressed sensing (CS). The CS theory of recoverability and stability of sparse solutions to underdetermined linear inverse problems has rapidly evolved during the last years. We show that all currently available CS concepts predict an extremely poor worst case performance, and a low expected performance of the TomoPIV measurement system, indicating why low particle densities only are currently used by engineers in practice. Simulations demonstrate however that slight random perturbations of the TomoPIV measurement matrix considerably boost both worst-case and expected reconstruction performance. This finding is interesting for CS theory and for the design of TomoPIV measurement systems in practice.
date: 2009
type: Preprint
type: info:eu-repo/semantics/preprint
type: NonPeerReviewed
format: application/pdf
identifier: https://archiv.ub.uni-heidelberg.de/volltextserverhttps://archiv.ub.uni-heidelberg.de/volltextserver/9760/1/puma09_submission.pdf
identifier: DOI:10.11588/heidok.00009760
identifier: urn:nbn:de:bsz:16-opus-97604
identifier:   Petra, Stefania ; Schnörr, Christoph  (2009) TomoPIV meets Compressed Sensing.  [Preprint]     
relation: https://archiv.ub.uni-heidelberg.de/volltextserver/9760/
rights: info:eu-repo/semantics/openAccess
rights: http://archiv.ub.uni-heidelberg.de/volltextserver/help/license_urhg.html
language: eng