Computational ghost imaging with the human brain

Wang, G. and Faccio, D. (2023) Computational ghost imaging with the human brain. Intelligent Computing, 2, 0014. (doi: 10.34133/icomputing.0014)

Abstract

Brain–computer interfaces are enabling a range of new possibilities and routes for augmenting human capability. Here, we propose brain–computer interfaces as a route towards forms of computation, i.e., computational imaging, that blend the brain with external silicon processing. We demonstrate ghost imaging of a hidden scene using the human visual system that is combined with an adaptive computational imaging scheme. This is achieved through a projection pattern “carving” technique that relies on real-time feedback from the brain to modify patterns at the light projector, thus enabling more efficient and higher-resolution imaging. This brain–computer connectivity demonstrates a form of augmented human computation that could, in the future, extend the sensing range of human vision and provide new approaches to the study of the neurophysics of human perception. As an example, we illustrate a simple experiment whereby image reconstruction quality is affected by simultaneous conscious processing and readout of the perceived light intensities.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Wang, Gao and Faccio, Professor Daniele
• Authors: Wang, G., and Faccio, D.
• College/School: College of Science and Engineering > School of Physics and Astronomy
• Journal Name: Intelligent Computing
• Publisher: American Association for the Advancement of Science
• ISSN: 2771-5892
• ISSN (Online): 2771-5892
• Published Online: 24 February 2023
• Copyright Holders: Copyright © 2023 Gao Wang and Daniele Faccio Exclusive licensee Zhejiang Lab
• First Published: First published in Intelligent Computing 2: 0014
• Publisher Policy: Reproduced under a Creative Commons License
• Data DOI: 10.5525/gla.researchdata.1368

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
305153		RAEng Chair Emerging Technologies	Daniele Faccio	Royal Academy of Engineering (RAE)	CiET1819/20	P&S - Physics & Astronomy
305567		QuantIC - The UK Quantum Technoogy Hub in Quantum Enhanced Imaging	Miles Padgett	Engineering and Physical Sciences Research Council (EPSRC)	EP/T00097X/1	P&S - Physics & Astronomy