Photon-efficient computational imaging with single-photon avalanche diode (SPAD) arrays

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.

Bibliographic Details
Main Author: Rumbley, Sarah (Sarah E.)
Other Authors: Jeffrey H. Shapiro.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2016
Subjects:
Online Access:http://hdl.handle.net/1721.1/106005
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author Rumbley, Sarah (Sarah E.)
author2 Jeffrey H. Shapiro.
author_facet Jeffrey H. Shapiro.
Rumbley, Sarah (Sarah E.)
author_sort Rumbley, Sarah (Sarah E.)
collection MIT
description Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.
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spelling mit-1721.1/1060052019-04-12T17:22:08Z Photon-efficient computational imaging with single-photon avalanche diode (SPAD) arrays Rumbley, Sarah (Sarah E.) Jeffrey H. Shapiro. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages 77-78). Single-photon avalanche diodes (SPADs) are highly sensitive photodetectors that enable LIDAR imaging at extremely low photon flux levels. While conventional image formation methods require hundreds or thousands of photon detections per pixel to suppress noise, a recent computational approach achieves comparable results when forming reflectivity and depth images from on the order of 1 photon detection per pixel. This method uses the statistics underlying photon detections, along with the assumption that depth and reflectivity are spatially correlated in natural scenes, to perform noise censoring and regularized maximum-likelihood estimation. We expand on this research by adapting the method for use with SPAD arrays, accounting for the spatial non-uniformity of imaging parameters and the effects of crosstalk. We develop statistical models that incorporate these non-idealities, and present a statistical method for censoring crosstalk detections. We show results that demonstrate the performance of our method on simulated data with a range of imaging parameters. by Sarah Rumbley. M. Eng. 2016-12-22T15:18:16Z 2016-12-22T15:18:16Z 2015 2015 Thesis http://hdl.handle.net/1721.1/106005 965799484 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 78 pages application/pdf Massachusetts Institute of Technology
spellingShingle Electrical Engineering and Computer Science.
Rumbley, Sarah (Sarah E.)
Photon-efficient computational imaging with single-photon avalanche diode (SPAD) arrays
title Photon-efficient computational imaging with single-photon avalanche diode (SPAD) arrays
title_full Photon-efficient computational imaging with single-photon avalanche diode (SPAD) arrays
title_fullStr Photon-efficient computational imaging with single-photon avalanche diode (SPAD) arrays
title_full_unstemmed Photon-efficient computational imaging with single-photon avalanche diode (SPAD) arrays
title_short Photon-efficient computational imaging with single-photon avalanche diode (SPAD) arrays
title_sort photon efficient computational imaging with single photon avalanche diode spad arrays
topic Electrical Engineering and Computer Science.
url http://hdl.handle.net/1721.1/106005
work_keys_str_mv AT rumbleysarahsarahe photonefficientcomputationalimagingwithsinglephotonavalanchediodespadarrays