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 publication2005 Conference on Lasers and Electro-Optics, CLEO
Pages2345-2347
Number of pages3
StatePublished - Dec 1 2005
Event2005 Conference on Lasers and Electro-Optics, CLEO - Baltimore, MD, United States
Duration: May 22 2005May 27 2005

Publication series

Name2005 Conference on Lasers and Electro-Optics, CLEO
Volume3

Other

Other2005 Conference on Lasers and Electro-Optics, CLEO
CountryUnited States
CityBaltimore, MD
Period5/22/055/27/05

ASJC Scopus subject areas

  • Engineering(all)

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