Maximum-likelihood surface reconstruction with Viterbi algorithm for volume holographic profilometry

Wenyang Sun, George Barbastathis, Mark A. Neifeld

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We use maximum-likelihood (ML) estimation to clean up the depth-variant image blur in volume holographic profilometry and to reconstruct the surface with high accuracy. Viterbi algorithm is used in ML estimation to reduce computational complexity and bit error rate.

Original languageEnglish (US)
Title of host publicationConference on Lasers and Electro-Optics, CLEO 2005
PublisherOptical Society of America
ISBN (Print)1557527709, 9781557527707
StatePublished - Jan 1 2005
EventConference on Lasers and Electro-Optics, CLEO 2005 - Baltimore, MD, United States
Duration: May 22 2005May 22 2005

Publication series

NameOptics InfoBase Conference Papers
ISSN (Electronic)2162-2701

Other

OtherConference on Lasers and Electro-Optics, CLEO 2005
CountryUnited States
CityBaltimore, MD
Period5/22/055/22/05

ASJC Scopus subject areas

  • Instrumentation
  • Atomic and Molecular Physics, and Optics

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  • Cite this

    Sun, W., Barbastathis, G., & Neifeld, M. A. (2005). Maximum-likelihood surface reconstruction with Viterbi algorithm for volume holographic profilometry. In Conference on Lasers and Electro-Optics, CLEO 2005 (Optics InfoBase Conference Papers). Optical Society of America.