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arXiv · 0807.3209

Bayes-optimal inverse halftoning and statistical mechanics of the Q-Ising model

Yohei Saika·Jun-ichi Inoue·Hiroyuki Tanaka·Masato Okada
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Abstract

On the basis of statistical mechanics of the Q-Ising model, we formulate the Bayesian inference to the problem of inverse halftoning, which is the inverse process of representing gray-scales in images by means of black and white dots. Using Monte Carlo simulations, we investigate statistical properties of the inverse process, especially, we reveal the condition of the Bayes-optimal solution for which the mean-square error takes its minimum. The numerical result is qualitatively confirmed by analysis of the infinite-range model. As demonstrations of our approach, we apply the method to retrieve a grayscale image, such as standard image `Lenna', from the halftoned version. We find that the Bayes-optimal solution gives a fine restored grayscale image which is very close to the original.

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Yohei Saika, Jun-ichi Inoue, Hiroyuki Tanaka, Masato Okada. 2008-07-21. Bayes-optimal inverse halftoning and statistical mechanics of the Q-Ising model. https://doi.org/10.2478/s11534-009-0066-0

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