Inherent dose-reduction potential of classical ghost imaging

Andrew M. Kingston, Wilfred K. Fullagar, Glenn R. Myers, Daishi Adams, Daniele Pelliccia, and David M. Paganin
Phys. Rev. A 103, 033503 – Published 5 March 2021

Abstract

Classical ghost imaging is a computational imaging technique that employs patterned illumination. It is very similar in concept to the single-pixel camera in that an image may be reconstructed from a set of measurements even though all imaging photons or particles that pass through that sample are never recorded with a position resolving detector. The method was first conceived and applied for visible-wavelength photons and was subsequently translated to other probes such as x rays, atomic beams, electrons, and neutrons. In the context of classical ghost imaging using penetrating probes that enable transmission measurement, we here consider several questions relating to the achievable signal-to-noise ratio (SNR). This is compared with the SNR for conventional imaging under scenarios of constant radiation dose and constant experiment time, considering both photon shot noise and per-measurement electronic readout noise. We show that inherent improved SNR capabilities of classical ghost imaging are limited to a subset of these scenarios and are actually due to increased dose (Fellgett advantage). An explanation is also presented for recent results published in the literature that are not consistent with these findings.

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  • Received 6 September 2020
  • Accepted 3 February 2021

DOI:https://doi.org/10.1103/PhysRevA.103.033503

©2021 American Physical Society

Physics Subject Headings (PhySH)

Atomic, Molecular & OpticalCondensed Matter, Materials & Applied Physics

Authors & Affiliations

Andrew M. Kingston*, Wilfred K. Fullagar, Glenn R. Myers, and Daishi Adams

  • Department of Applied Mathematics, Research School of Physics, The Australian National University, Canberra, ACT 2601, Australia

Daniele Pelliccia

  • Instruments & Data Tools Pty Ltd, Victoria 3178, Australia

David M. Paganin

  • School of Physics and Astronomy, Monash University, VIC 3800, Australia

  • *Also at CTLab: National Laboratory for Micro Computed-Tomography, Advanced Imaging Precinct, The Australian National University, Canberra, ACT 2601, Australia; andrew.kingston@anu.edu.au

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Issue

Vol. 103, Iss. 3 — March 2021

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