Presentation 2006-07-14
Statistical Analysis of Hyperparameter Estimation in Probabilistic Image Processing
Hikaru KURASAWA, Kazuyuki TANAKA,
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Abstract(in English) We investigate dynamics of hyperparameter estimations in probabilistic image restorations by using EM Algorithm for Markov process in the infinite range model. Probabilistic image restorations are formulated by using the Bayes formula when the prior probability is assumed to be the infinite range model and the degradation process is set to be the Gaussian channel. The dynamics are analyzed statistically by means of the generating functional method for path integral representation in Markov process. The results are compared with the ones obtained by using the replica method for the formulation of the master equation which corresponds to the case of non-synchronized update algorithms.
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Keyword(in English) Image Processing / Markov Random Fields / Statistical Method / Dynamics / Statistical Mechanics / Path Integral Representation / Generating Functional Analysis / Hyperparameter Estimation / EM Algorithm
Paper # NC2006-39
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Committee NC
Conference Date 2006/7/7(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Statistical Analysis of Hyperparameter Estimation in Probabilistic Image Processing
Sub Title (in English)
Keyword(1) Image Processing
Keyword(2) Markov Random Fields
Keyword(3) Statistical Method
Keyword(4) Dynamics
Keyword(5) Statistical Mechanics
Keyword(6) Path Integral Representation
Keyword(7) Generating Functional Analysis
Keyword(8) Hyperparameter Estimation
Keyword(9) EM Algorithm
1st Author's Name Hikaru KURASAWA
1st Author's Affiliation Graduate School of Information Sciences, Tohoku University()
2nd Author's Name Kazuyuki TANAKA
2nd Author's Affiliation Graduate School of Information Sciences, Tohoku University
Date 2006-07-14
Paper # NC2006-39
Volume (vol) vol.106
Number (no) 163
Page pp.pp.-
#Pages 6
Date of Issue