000231982 001__ 231982
000231982 005__ 20190317000848.0
000231982 020__ $$a978-1-5386-4658-8
000231982 037__ $$aCONF
000231982 245__ $$aPulse-Stream Models In Time-Of-Flight Imaging
000231982 269__ $$a2018
000231982 260__ $$bIEEE$$c2018
000231982 336__ $$aConference Papers
000231982 520__ $$aThis paper considers the problem of reconstructing raw signals from random projections in the context of time-of-flight imaging with an array of sensors. It presents a new signal model, coined as multi-channel pulse-stream model, which exploits pulse-stream models and accounts for additional structure induced by inter-sensor dependencies. We propose a sampling theorem and a reconstruction algorithm, based on l1-minimization, for signals belonging to such a model. We demonstrate the benefits of the proposed approach by means of numerical simulations and on a real nondestructive- evaluation application where the peak-signal-to-noise ratio is increased by 3 dB compared to standard compressed-sensing strategies.
000231982 6531_ $$aCompressed sensing
000231982 6531_ $$asparsity
000231982 6531_ $$aarray imaging
000231982 6531_ $$aultrasound
000231982 700__ $$0248789$$aBesson, Adrien Georges Jean$$g214640
000231982 700__ $$0248238$$aPerdios, Dimitris$$g179668
000231982 700__ $$0240427$$aWiaux, Yves$$g163268
000231982 700__ $$0240323$$aThiran, Jean-Philippe$$g115534
000231982 7112_ $$a2018 IEEE International Conference on Acoustics, Speech and Signal Processing$$cCalgary, Alberta, Canada$$dApril 15-20, 2018
000231982 773__ $$q3389-3393$$tIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
000231982 8564_ $$s373082$$uhttps://infoscience.epfl.ch/record/231982/files/icassp_2018.pdf$$yPreprint$$zPreprint
000231982 8564_ $$s373220$$uhttps://infoscience.epfl.ch/record/231982/files/icassp_2018_final.pdf$$zFinal
000231982 8564_ $$s1553609$$uhttps://infoscience.epfl.ch/record/231982/files/icassp_2018_final.pdf?subformat=pdfa$$xpdfa$$zFinal
000231982 8560_ $$fadrien.besson@epfl.ch
000231982 909C0 $$0252394$$pLTS5$$xU10954
000231982 909CO $$ooai:infoscience.tind.io:231982$$pconf$$pSTI$$qGLOBAL_SET
000231982 917Z8 $$x214640
000231982 917Z8 $$x214640
000231982 917Z8 $$x214640
000231982 917Z8 $$x115534
000231982 937__ $$aEPFL-CONF-231982
000231982 973__ $$aEPFL$$rREVIEWED
000231982 980__ $$aCONF