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.
© 2005 Optical Society of America
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