Uncertainty in Artificial Intelligence
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A Factorized Variational Technique for Phase Unwrapping in Markov Random Fields
Kannan Achan, Brendan Frey, Ralf Koetter
Some types of medical and topographic imaging device produce images in which the pixel values are "phase-wrapped", i.e. measured modulus a known scalar. Phase unwrapping can be viewed as the problem of inferring the number of shifts between each and every pair of neighboring pixels, subject to an a priori preference for smooth surfaces, and subject to a zero curl constraint, which requires that the shifts must sum to 0 around every loop. We formulate phase unwrapping as a mean field inference problem in a Markov network, where the prior favors the zero curl constraint. We compare our mean field technique with the least squares method on a synthetic 100x100 image, and give results on a 512x512 synthetic aperture radar image from Sandia National Laboratories.
Pages: 1-6
PS Link:
PDF Link: /papers/01/p1-achan.pdf
AUTHOR = "Kannan Achan and Brendan Frey and Ralf Koetter",
TITLE = "A Factorized Variational Technique for Phase Unwrapping in Markov Random Fields",
BOOKTITLE = "Proceedings of the Seventeenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-01)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2001",
PAGES = "1--6"

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