Low Photon Count Phase Retrieval Using Deep Learning

Alexandre Goy, Kwabena Arthur, Shuai Li, and George Barbastathis
Phys. Rev. Lett. 121, 243902 – Published 12 December 2018
PDFHTMLExport Citation

Abstract

Imaging systems’ performance at low light intensity is affected by shot noise, which becomes increasingly strong as the power of the light source decreases. In this Letter, we experimentally demonstrate the use of deep neural networks to recover objects illuminated with weak light and demonstrate better performance than with the classical Gerchberg-Saxton phase retrieval algorithm for equivalent signal over noise ratio. The prior contained in the training image set can be leveraged by the deep neural network to detect features with a signal over noise ratio close to one. We apply this principle to a phase retrieval problem and show successful recovery of the object’s most salient features with as little as one photon per detector pixel on average in the illumination beam. We also show that the phase reconstruction is significantly improved by training the neural network with an initial estimate of the object, as opposed to training it with the raw intensity measurement.

  • Figure
  • Figure
  • Figure
  • Received 25 June 2018

DOI:https://doi.org/10.1103/PhysRevLett.121.243902

© 2018 American Physical Society

Physics Subject Headings (PhySH)

Atomic, Molecular & Optical

Authors & Affiliations

Alexandre Goy*, Kwabena Arthur, Shuai Li, and George Barbastathis

  • Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

  • *agoy@mit.edu
  • Also at: Singapore-MIT Alliance for Research and 284 Technology (SMART) Centre, Singapore 117543, Singapore.

Article Text (Subscription Required)

Click to Expand

Supplemental Material (Subscription Required)

Click to Expand

References (Subscription Required)

Click to Expand
Issue

Vol. 121, Iss. 24 — 14 December 2018

Reuse & Permissions
Access Options
CHORUS

Article Available via CHORUS

Download Accepted Manuscript
Author publication services for translation and copyediting assistance advertisement

Authorization Required


×
×

Images

×

Sign up to receive regular email alerts from Physical Review Letters

Log In

Cancel
×

Search


Article Lookup

Paste a citation or DOI

Enter a citation
×