Description: 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.
File list (Check if you may need any files):
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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