This 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 reconstruc- tion 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 non- destructive-evaluation application where the peak-signal-to-noise- ratio is increased by 3 dB compared to standard compressed-sensing strategies.
|Title of host publication||2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)|
|Number of pages||5|
|Publication status||Published - 13 Sep 2018|
|Name||International Conference on Acoustics, Speech and Signal Processing|