Strong Markov random field model.
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Abstract
The strong Markov random field (strong-MRF) model is a submodel of the more general MRF-Gibbs model. The strong-MRF model defines a system whose field is Markovian with respect to a defined neighborhood, and all subneighborhoods are also Markovian. A checkerboard pattern is a perfect example of a strong Markovian system. Although the strong Markovian system requires a more stringent assumption about the field, it does have some very nice mathematical properties. One mathematical property is the ability to define the strong-MRF model with respect to its marginal distributions over the cliques. Also, a direct equivalence to the Analysis-of-Variance (ANOVA) log-linear construction can be proven. From this proof, the general ANOVA log-linear construction formula is acquired.
Medical subject headings
- Algorithms
- Artificial Intelligence
- Image Interpretation, Computer-Assisted
- Markov Chains
- Models, Statistical
- Pattern Recognition, Automated
- Signal Processing, Computer-Assisted