Kazuyuki Tanaka et al 2003 J. Phys. A: Math. Gen. 36 11023 doi:10.1088/0305-4470/36/43/025
Kazuyuki Tanaka1, Jun-ichi Inoue2 and D M Titterington3
Show affiliationsThe framework of Bayesian image restoration for multi-valued images by means of the Q-Ising model with nearest-neighbour interactions is presented. 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 grey-level images, the Q-Ising model can give us good results.
05.50.+q Lattice theory and statistics (Ising, Potts, etc.)
62C10 Bayesian problems; characterization of Bayes procedures
82B20 Lattice systems (Ising, dimer, Potts, etc.) and systems on graphs
Issue 43 (31 October 2003)
Received 31 March 2003, in final form 1 August 2003
Published 15 October 2003
Kazuyuki Tanaka et al 2003 J. Phys. A: Math. Gen. 36 11023
R W Boswell 1985 Plasma Phys. Control. Fusion 27 405
Toshiyuki Tanaka 2009 J. Phys.: Conf. Ser. 143 012020
Michael Daniel 2006 Phys. Educ. 41 119
Frank E Harris 2002 J. Phys.: Condens. Matter 14 621
W K Hensinger et al 2000 J. Opt. B: Quantum Semiclass. Opt. 2 659
John W Conklin et al 2009 J. Phys.: Conf. Ser. 154 012019
Daniel E Barber and J David Carlson 2009 J. Phys.: Conf. Ser. 149 012035
Tomo Saito et al 2009 J. Phys.: Conf. Ser. 165 012009
Christopher White (on behalf of the Daya Bay Collaboration) 2008 J. Phys.: Conf. Ser. 136 022012