A new, to our knowledge, algorithm for the phase unwrapping
(PU) problem that is based on stochastic relaxation is proposed and
analyzed. Unlike regularization schemes previously proposed to
handle this problem, our approach dispells the following two
assumptions about the solution: a Gaussian model for noise and the
magnitude of the true phase-field gradient’s being less than π
everywhere. We formulate PU as a constrained optimization problem
for the field of integer multiples of 2π, which must be added to the
wrapped phase gradient to recover the true phase gradient. By
solving the optimization problem using simulated annealing with
constraints, one can obtain a consistent solution under difficult
conditions resulting from noise and undersampling. Results from
synthetic test images are reported.
© 1998 Optical Society of America
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