Regularization methods for processing fringe-pattern images

A powerful technique for processing fringe-pattern images is based on Bayes ian estimation theory with prior Markov random-field models. In this approa ch the solution of a processing problem is characterized as the minimizer o f a cost function with terms that specify that the solution should be compa tible with the available observations and terms that impose certain (prior) constraints on the solution. We show that, by the appropriate choice of th ese terms, one can use this approach in almost every processing step for ac curate and robust interferogram demodulation and phase unwrapping. (C) 1999 Optical Society of America.