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Massachusetts Institute of Technology

Computational time-resolved imaging

Abstract

dc:description.abstract

Classical photography uses steady-state illumination and light sensing with focusing optics to capture scene reflectivity as images; temporal variations of the light field are not exploited. This thesis explores the use of time-varying optical illumination and time-resolved sensing along with signal modeling and computational reconstruction. Its purpose is to create new imaging modalities, and to demonstrate high-quality imaging in cases in which traditional techniques fail to even form degraded imagery. The principal contributions in this thesis are the derivation of physically-accurate signal models for the scene's response to timevarying illumination and the photodetection statistics of the sensor, and the combining of these models with computationally tractable signal recovery algorithms leading to image formation. In active optical imaging setups, we use computational time-resolved imaging to experimentally demonstrate: non line-of-sight imaging or looking around corners, in which only diffusely scattered light was used to image a hidden plane which was completely occluded from both the light source and the sensor; single-pixel 3D imaging or compressive depth acquisition, in which accurate depth maps were obtained using a single, non-spatially resolving bucket detector in combination with a spatial light modulator; and high-photon efficiency imaging including first-photon imaging, in which high-quality 3D and reflectivity images were formed using only the first detected photon at each sensor pixel despite the presence of high levels of background light.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kirmani, Ghulam A. (Ghulam Ahmed)
Advisor dc:contributor.advisor
  • Jeffrey H. Shapiro and Vivek K Goyal.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • 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.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/97803
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/97803

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Kirmani, Ghulam A. (Ghulam Ahmed). Computational time-resolved imaging. Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/97803