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.
Maximum-likelihood surface reconstruction with Viterbi algorithm for volume holographic profilometry
(CLEO). Conference on Lasers and Electro-Optics, 2005. ; 3 ; 2345-2347 Vol. 3
2005-01-01
1595194 byte
Conference paper
Electronic Resource
English
Maximum-Likelihood Surface Reconstruction with Viterbi Algorithm for Volume Holographic Profilometry
British Library Conference Proceedings | 2005
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