Loopy Belief Propagation on MRFs in ITK
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/3253
This code provides a base implementation of Loopy Belief Propagation on MRFs in ITK. We use binary image denoising as an example problem to demonstrate this code.

This document is intended only to describe the implementation, not the theory. A complete tutorial on loopy belief propagation on MRFs is available here:

https://github.com/daviddoria/Tutorials/blob/master/BeliefPropagation/BeliefPropagation.pdf?raw=true

The code at the time of this submission is here:
https://github.com/daviddoria/BinaryDenoising/commit/e8bd152723584c3af7e30b5e529b8a80f2f2ee5c

And the latest version will be here:
https://github.com/daviddoria/BinaryDenoising


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Categories: Density Estimation, Image, Iterative clustering, Probability
Keywords: belief propagation, loopy belief propagation, denoising, mrf, graph, graphical model, inference
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