Abstract: On the basis of Bayesian inference using the
maximizer of the posterior marginal estimate, we carry out phase
unwrapping using multiple interferograms via generalized mean-field
theory. Numerical calculations for a typical wave-front in remote
sensing using the synthetic aperture radar interferometry, phase
diagram in hyper-parameter space clarifies that the present method
succeeds in phase unwrapping perfectly under the constraint of
surface- consistency condition, if the interferograms are not corrupted
by any noises. Also, we find that prior is useful for extending a phase
in which phase unwrapping under the constraint of the
surface-consistency condition. These results are quantitatively
confirmed by the Monte Carlo simulation.