Markov random field based image segmentation matlab source code, including the ICM iteration conditions for solving the maximum a posteriori probability model algorithm has been tested.

MRFtoyexample\MRFtoyexample\addNoise.m
.............\.............\computeBeliefs.m
.............\.............\gaussplot.m
.............\.............\getCliqueProb.m
.............\.............\getLogProb.m
.............\.............\getPropMat.m
.............\.............\getRasterNeighbors.m
.............\.............\ICM.m
.............\.............\initBPMessages.m
.............\.............\initICM.m
.............\.............\initLocalEvidence.m
.............\.............\initMRF.m
.............\.............\initNodes.m
.............\.............\initPaths.m
.............\.............\ipf.m
.............\.............\marginals2image.m
.............\.............\multMessages.m
.............\.............\oneIterBP.m
.............\.............\runBP.m
.............\.............\showIm.m
.............\.............\states2image.m
.............\.............\testMRF.m
.............\.............\utAxisAngleToRotmat.m
.............\.............\utCropImageToPowerOfTwo.m
.............\.............\utFilename.m
.............\.............\utIf.m
.............\.............\utIsScalarBoolean.m
.............\.............\utIsScalarInteger.m
.............\.............\utIsScalarReal.m
.............\.............\utIsSingleString.m
.............\.............\utNormalize.m
.............\.............\utParseArgs.m
.............\.............\utReadPnm.m
.............\.............\utRotmatToAxisAngle.m
.............\.............\utSafeInverse.m
.............\.............\utSafeMult.m
.............\.............\utSigmoid.m
.............\.............\utWritePnm.m
.............\MRFtoyexample
MRFtoyexample

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