eprintid: 9760
rev_number: 42
eprint_status: archive
userid: 1
dir: disk0/00/00/97/60
datestamp: 2009-08-17 07:34:45
lastmod: 2016-01-21 04:30:13
status_changed: 2012-08-14 15:30:30
type: preprint
metadata_visibility: show
creators_name: Petra, Stefania
creators_name: Schnörr, Christoph
title: TomoPIV meets Compressed Sensing
ispublished: pub
subjects: ddc-510
divisions: i-708000
keywords: compressed sensing , underdetermined systems of linear equations , positivity constraints in ill-posed problems , sparsest solution , TomoPIV
abstract: 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.
abstract_translated_lang: eng
date: 2009
date_type: published
id_scheme: DOI
id_number: 10.11588/heidok.00009760
portal_cluster_id: p-iwrpp
portal_order: 09760
ppn_swb: 1648297579
own_urn: urn:nbn:de:bsz:16-opus-97604
language: eng
bibsort: PETRASTEFATOMOPIVMEE2009
full_text_status: public
series: IWR-Preprints
citation:   Petra, Stefania ; Schnörr, Christoph  (2009) TomoPIV meets Compressed Sensing.  [Preprint]     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/9760/1/puma09_submission.pdf