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Massachusetts Institute of Technology

Light field applications to 3-dimensional surface imaging

Abstract

dc:description.abstract

The structure of light around a scene may be contained in a 4-dimensional array known as a light field. This thesis describes methods for acquiring and manipulating light fields for applications in 3-dimensional imaging. By actively sampling parts of the wavefront impinging on a lens, or using microlens arrays and patterned sinusoidal masks to modulate the rays reaching a camera, both the spatial distribution and directionality of light may be captured to produce light fields. Simple depth estimation algorithms using stereo and focus measures are then applied to recover quantitative depth information. Experiments on real-world light fields demonstrate their utility in performing digital refocusing, reconstructing occluded objects as well as accurately estimating depth and shape. The performance of the algorithms developed are discussed theoretically and compared empirically.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Dept. of Mechanical Engineering.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2009

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Hong, Wenxian
Advisor dc:contributor.advisor
  • Douglas P. Hart.

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/1721.1/54540
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/54540

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

Hong, Wenxian. Light field applications to 3-dimensional surface imaging. Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/54540