Single-pixel, single-photon three-dimensional imaging

Musarra, Gabriella (2020) Single-pixel, single-photon three-dimensional imaging. PhD thesis, University of Glasgow.

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Abstract

The 3D recovery of a scene is a crucial task with many real-life applications such as self-driving vehicles, X-ray tomography and virtual reality. The recent development of time-resolving detectors sensible to single photons allowed the recovery of the 3D information at high frame rate with unprecedented capabilities. Combined with a timing system, single-photon sensitive detectors
allow the 3D image recovery by measuring the Time-of-Flight (ToF) of the photons scattered back by the scene with a millimetre depth resolution.
Current ToF 3D imaging techniques rely on scanning detection systems or multi-pixel sensor.
Here, we discuss an approach to simplify the hardware complexity of the current 3D imaging ToF techniques using a single-pixel, single-photon sensitive detector and computational imaging algorithms. The 3D imaging approaches discussed in this thesis do not require mechanical moving
parts as in standard Lidar systems. The single-pixel detector allows to reduce the pixel complexity to a single unit and offers several advantages in terms of size, flexibility, wavelength range and cost. The experimental results demonstrate the 3D image recovery of hidden scenes with a subsecond
acquisition time, allowing also non-line-of-sight scenes 3D recovery in real-time. We also introduce the concept of intelligent Lidar, a 3D imaging paradigm based uniquely on the temporal trace of the return photons and a data-driven 3D retrieval algorithm.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Keywords: 3D imaging, single-pixel imaging, neural networks, computational imaging.
Subjects: Q Science > QC Physics
Colleges/Schools: College of Science and Engineering > School of Physics and Astronomy
Supervisor's Name: Faccio, Prof. Daniele
Date of Award: 2020
Depositing User: Miss Gabriella Musarra
Unique ID: glathesis:2020-81446
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 02 Jul 2020 06:52
Last Modified: 02 Jul 2020 07:04
URI: http://theses.gla.ac.uk/id/eprint/81446
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