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 2006
PublisherOptical Society of America
ISBN (Print)1557528136, 9781557528131
StatePublished - Jan 1 2006
EventConference on Lasers and Electro-Optics, CLEO 2006 - Long Beach, CA, United States
Duration: May 21 2006May 21 2006

Publication series

NameOptics InfoBase Conference Papers
ISSN (Electronic)2162-2701

Other

OtherConference on Lasers and Electro-Optics, CLEO 2006
CountryUnited States
CityLong Beach, CA
Period5/21/065/21/06

ASJC Scopus subject areas

  • Instrumentation
  • Atomic and Molecular Physics, and Optics

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  • Cite this

    Sun, W., Barbastathis, G., & Neifeld, M. A. (2006). Maximum-likelihood surface reconstruction with Viterbi algorithm for volume holographic profilometry. In Conference on Lasers and Electro-Optics, CLEO 2006 (Optics InfoBase Conference Papers). Optical Society of America.