Abstract
A novel means of quantitatively assessing the performance of a
phase-shifting interferometer is further investigated. We show how
maximum-likelihood estimation theory can be used to estimate the
surface profile from the general case of M noisy,
phase-shifted measurements. Monte Carlo experiments show that the
maximum-likelihood estimator is unbiased and efficient, achieving the
theoretical Cramér–Rao lower bound on the variance of the
error. We then use Monte Carlo experiments to compare the
performance of the maximum-likelihood estimator with that of two
conventional algorithms.
© 1998 Optical Society of America
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