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
Abstract:
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.
Keywords:
Pages: 1-6
PS Link:
PDF Link: /papers/01/p1-achan.pdf
BibTex:
@INPROCEEDINGS{Achan01,
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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