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Probabilistic image processing by means of Bethe approximation for the Q-Ising model
| Content Provider | Semantic Scholar |
|---|---|
| Author | Tanaka, Kazuyuki |
| Copyright Year | 2003 |
| Abstract | The framework is presented of Bayesian image restoration for multivalued images by means of the Q-Ising model with nearest-neighbor interactions. Hyperparameters in the probabilistic model are determined so as to maximize the marginal likelihood. A practical algorithm is described for multi-valued image restoration based on the Bethe approximation. The algorithm corresponds to loopy belief propagation in artificial intelligence. We conclude that, in real world gray-level images, the Q-Ising model can give us good results. PACS numbers: 02.50-r, 02.50.Cw, 02.50.Tt, 05.20.-y, 05.50.+q, 75.10.Nr, 89.70.+c § To whom correspondence should be addressed (kazu@statp.is.tohoku.ac.jp) Probabilistic image processing by the Q-Ising model 2 |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.smapip.is.tohoku.ac.jp/~kazu/Tanaka-Inoue-Titterington-2003a/main.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Algorithm Approximation Artificial intelligence Belief propagation Casio Loopy Circuit restoration Image processing Image restoration Interaction Ising model JSP model 2 architecture Marginal model Numerous Physics and Astronomy Classification Scheme Software propagation Statistical model |
| Content Type | Text |
| Resource Type | Article |
