Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
1999-04-08
Physics
Condensed Matter
Disordered Systems and Neural Networks
RevTex 13 pages, 10 figures
Scientific paper
10.1103/PhysRevE.60.2547
We report on the image reconstruction (IR) problem by making use of the random chiral q-state Potts model, whose Hamiltonian possesses the same gauge invariance as the usual Ising spin glass model. We show that the pixel representation by means of the Potts variables is suitable for the gray-scale level image which can not be represented by the Ising model. We find that the IR quality is highly improved by the presence of a glassy term, besides the usual ferromagnetic term under random external fields, as very recently pointed out by Nishimori and Wong. We give the exact solution of the infinite range model with q=3, the three gray-scale level case. In order to check our analytical result and the efficiency of our model, 2D Monte Carlo simulations have been carried out on real-world pictures with three and eight gray-scale levels.
Carlucci Domenico M.
Inoue Jun'ichi
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