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 - 2005
Externally publishedYes
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
Country/TerritoryUnited States
CityBaltimore, MD
Period5/22/055/22/05

ASJC Scopus subject areas

  • Instrumentation
  • Atomic and Molecular Physics, and Optics

Fingerprint

Dive into the research topics of 'Maximum-likelihood surface reconstruction with Viterbi algorithm for volume holographic profilometry'. Together they form a unique fingerprint.

Cite this