Mean Field Decomposition of A Posteriori Probability for MRF-Based Image Segmentation : Unsupervised Multispectral Textured Image Segmentation
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概要
- 論文の詳細を見る
This paper proposes a Markov random field (MRF) model-based method for unsupervised segmentation of multispectral images consisting of multiple textures. To model such textured images, a hierarchical MRF is used with two layers, the first layer representing an unobservable region image and the second layer representing multiple textures which cover each region. This method uses the Expectation and Maximization (EM) method for model parameter estimation, where in order to overcome the well-noticed computational problem in the expectation step, we approximate the Baum function using mean-field-based decomposition of a posteriori probability. Given provisionally estimated parameters at each iteration in the EM method, a provisional segmentation is carried out using local a posteriori probability (LAP) of each pixel's region label, which is derived by mean-field-based decomposition of a posteriori probability of the whole region image. Experiments show that the use of LAPs is essential to perform a good image segmentation.
- 社団法人電子情報通信学会の論文
- 1999-12-25
著者
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Zhang B
Key Laboratory For Polymeric Composite And Functional Materials Of Ministry Of Education Zhongshan U
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Zhang Bing
Key Laboratory For Polymeric Composite And Functional Materials Of Ministry Of Education Zhongshan U
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NODA Hideki
Department of Systems Design and Informatics, Kyushu Institute of Technology
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Zhang Bing
Kansai Advanced Research Center Communications Research Laboratory Ministry Of Posts And Telecommuni
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SHIRAZI Mehdi
Faculty of Information Science, Osaka Institute of Technology
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TAKAO Nobuteru
Department of E.E. and Computer Engineering, Kyushu Institute of Technology
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KAWAGUCHI Eiji
Department of E.E. and Computer Engineering, Kyushu Institute of Technology
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Shirazi Mehdi
Faculty Of Information Science Osaka Institute Of Technology
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Takao Nobuteru
Department Of E.e. And Computer Engineering Kyushu Institute Of Technology
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Kawaguchi Eiji
Department Of Computer Engineering Kyushu Institute Of Technology
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Zhang Bing
Research Center Of Materials Science Beijing Institute Of Technology
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Shirazi M
Communications Research Laboratory Keihanna Human Info-communications Research Center
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Shirazi Mehdi
Faculty Of Engineering Kyoto University
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Noda Hideki
Department Of Applied Biochemistry Faculty Of Applied Biological Science Hiroshima University
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