文件列表:

maerkefu\maerkf.m (2529, 2018-07-11)
Code\Gaussian noise Removal\blur_image.m (156, 2014-10-14)
Code\Gaussian noise Removal\main_restore.m (155, 2014-10-14)
Code\Gaussian noise Removal\original.jpg (63195, 2014-10-14)
Code\Gaussian noise Removal\restore_image.m (2094, 2014-10-14)
Code\Gaussian noise Removal\Untitled2.m (169, 2014-10-14)
Code\MRF_Edge\covmatrix.m (168, 2014-10-14)
Code\MRF_Edge\EnergyOfFeatureField.m (478, 2014-10-14)
Code\MRF_Edge\EnergyOfLabelField.m (396, 2014-10-14)
Code\MRF_Edge\foot_ulcer_0028.jpg (20189, 2014-10-14)
Code\MRF_Edge\GMM_parameter.m (250, 2014-10-14)
Code\MRF_Edge\ICM.m (766, 2014-10-14)
Code\MRF_Edge\imstack2vectors.m (907, 2014-10-14)
Code\MRF_Edge\leg_ulcers_0017.jpg (25814, 2014-10-14)
Code\MRF_Edge\leg_ulcers_0097.jpg (26267, 2014-10-14)
Code\MRF_Edge\leg_ulcer_case_2_7.jpg (32610, 2014-10-14)
Code\MRF_Edge\Main_seg.m (678, 2018-07-17)
Code\MRF_Edge\NeiX.m (709, 2014-10-14)
Code\wound.m (949, 2014-10-14)
Read Paper\00615858.pdf (466520, 2014-10-14)
Read Paper\00650883.pdf (214169, 2014-10-14)
Read Paper\00698638.pdf (108370, 2014-10-14)
Read Paper\00769356.pdf (164846, 2014-10-14)
Read Paper\04767596.pdf (9423103, 2014-10-14)
Read Paper\0903.3114.pdf (356544, 2014-10-14)
Read Paper\33.pdf (297026, 2014-10-14)
Read Paper\Besag86.pdf (6741486, 2014-10-14)
Read Paper\FigueiredoCVPR.pdf (1445440, 2014-10-14)
pdf (514674, 2014-10-14)
Read Paper\MRF.pdf (2492641, 2014-10-14)
Read Paper\mrfbook.pdf (7330392, 2014-10-14)
Read Paper\NOISE ijjvol2no3p3.pdf (330803, 2014-10-14)
Read Paper\pattrec99.pdf (946743, 2014-10-14)
... ...

In the initial 10-15 days of internship, I read research papers of IEEE and Elsevier to learn the basic concept of the MRF. After that I came to know that MRF is very useful in noise removal, image enhancement and image segmentation etc. I implemented a code in matlab, in main function one can give the number of iterations, as more the number of iterations more clear are the edges. It includes an ICM function which combines all other functions. Neix Function assigns the potential of a clique being well classified depending on its 8 neighbors. Function GMM parameter find sigma corresponding each pixel with the use of covariance function.

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