
Loopy Belief Propagation on MRFs in ITK
Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/3253 |
Published in The Insight Journal - 2011 January-June.
Submitted by David Doria on 03-01-2011.
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
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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