Presentation 2010/6/11
Bayesian Image Super-Resolution of Linear Degradation Model with a Compound Markov Random Field Prior
Takayuki KATSUKI, Akira TORII, Masato INOUE,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) Super-resolution is a technique to estimate higher resolution image from multiple low-resolution observed images. We treat Bayesian image super-resolution with a compound Markov random field prior. In preceding studies, point estimation by marginal likelihood maximization was employed on either degradation transformation parameters or high-resolution image. When both the hyper-parameters and those parameters are estimated simultaneously, such point estimation may cause over fitting problem since the flexibility will increase. In this report, we try high accurate estimation avoiding over fitting by estimating all parameters in Bayesian inference using a approximate method combining Taylor expansion and Laplace method with variational Bayesian method.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) super-resolution / compound Markov random field prior / Bayesian inference / variational Bayesian method
Paper # NC2010-10,NLP2010-10
Date of Issue

Conference Information
Committee NC
Conference Date 2010/6/11(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Bayesian Image Super-Resolution of Linear Degradation Model with a Compound Markov Random Field Prior
Sub Title (in English)
Keyword(1) super-resolution
Keyword(2) compound Markov random field prior
Keyword(3) Bayesian inference
Keyword(4) variational Bayesian method
1st Author's Name Takayuki KATSUKI
1st Author's Affiliation Department of Electrical Engineering and Bioscience, Graduate School of Advanced Science and Engineering, Waseda University()
2nd Author's Name Akira TORII
2nd Author's Affiliation Department of Electrical Engineering and Bioscience, Graduate School of Advanced Science and Engineering, Waseda University
3rd Author's Name Masato INOUE
3rd Author's Affiliation Department of Electrical Engineering and Bioscience, Graduate School of Advanced Science and Engineering, Waseda University
Date 2010/6/11
Paper # NC2010-10,NLP2010-10
Volume (vol) vol.110
Number (no) 83
Page pp.pp.-
#Pages 6
Date of Issue