Enhancing the recovery of a temporal sequence of images using joint deconvolution

Piergiorgio Caramazza, Kali Wilson, Geneviève Gariépy, Jonathan Leach, Stephen McLaughlin, Daniele Faccio, Yoann Altmann

Research output: Contribution to journalArticle

3 Citations (Scopus)
24 Downloads (Pure)

Abstract

In this work, we address the reconstruction of spatial patterns that are encoded in light fields associated with a series of light pulses emitted by a laser source and imaged using photon-counting cameras, with an intrinsic response significantly longer than the pulse delay. Adopting a Bayesian approach, we propose and demonstrate experimentally a novel joint temporal deconvolution algorithm taking advantage of the fact that single pulses are observed simultaneously by different pixels. Using an intensified CCD camera with a 1000-ps gate, stepped with 10-ps increments, we show the ability to resolve images that are separated by a 10-ps delay, four time better compared to standard deconvolution techniques.
Original languageEnglish
Article number5257
JournalScientific Reports
Volume8
DOIs
Publication statusPublished - 27 Mar 2018

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    Enhancing the recovery of a temporal sequence of images using joint deconvolution

    Faccio, D. F. A. (Creator) & Caramazza, P. (Creator), Heriot-Watt University, 2017

    Dataset

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