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J-GLOBAL ID：200902194776212335   Reference number：00A0089130

Mean Field Decomposition of A Posteriori Probability for MRF-Based Image Segmentation. Unsupervised Multispectral Textured Image Segmentation.

MRFに基づく画像領域分割のための事後確率の平均場分解 教師なしマルチスペクトルテクスチャ画像領域分割

Author (5)： NODA H (Kyushu Inst. Technol., Kitakyushu-shi, JPN) ,  SHIRAZI M N (Osaka Inst. Technol., Hirakata-shi, JPN) ,  ZHANG B (Communications Res. Lab., Ministry of Posts and Telecommunications of Japan, Kobe-shi, JPN) ,  TAKAO N (Kyushu Inst. Technol., Kitakyushu-shi, JPN) ,  KAWAGUCHI E (Kyushu Inst. Technol., Kitakyushu-shi, JPN)
Material： IEICE Transactions on Information and Systems (Institute of Electronics, Information and Communication Engineers)  (IEICE Trans Inf Syst (Inst Electron Inf Commun Eng))
Volume： E82-D  Issue： 12  Page： 1605-1611  Publication year： Dec. 25, 1999 
JST Material Number： L1371A  ISSN： 0916-8532  Document type： Article
Article type： 原著論文  Country of issue： Japan (JPN)  Language： ENGLISH (EN)

Thesaurus term： Markov process ,...
Semi thesaurus term： Markov random field

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JST classification (1)： Graphic and image processing in general  (JE04010I)

Reference (9)：

• WON, C. S. Unsupervised segmentation of noisy and textured images using Markov random fields. CVGIP: Graphical Models & Image Process. 1992, 54, 4, 308-328
• ZHANG, J. The mean field theory in EM procedures for Markov random fields. IEEE Trans. Signal Process. 1992, 40, 10, 2570-2583
• ZHANG, J. Maximumlikelihood parameter estimation for unsupervised stochastic model-based image segmentation. IEEE Trans. Image Processing. 1994, 3, 4, 404-420
• NODA, H. Data-driven segmentation of textured images using hierarchical Markov random fields. IEICE Trans. 1994, J77-D-II, 5, 922-930
• DEMPSTER, A. P. Maximum likelihood from incomplete data via the EM algorithm. J. Roy. Stat. Soc. 1977, 39, 1, 1-38

Terms in the title (8)： MRF ,  領域分割 ,  事後確率 ,  平均場 ,  分解 ,  教師 ,  マルチスペクトル ,  テクスチャ画像