Mean-field theory for grayscale texture synthesis using Gibbs random fields

Ibrahim M. Elfadel; Alan L. Yuille

doi:10.1117/12.48383

1 October 1991 Mean-field theory for grayscale texture synthesis using Gibbs random fields

Ibrahim M. Elfadel, Alan L. Yuille

Proceedings Volume 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision; (1991) https://doi.org/10.1117/12.48383
Event: San Diego, '91, 1991, San Diego, CA, United States

Abstract

This paper shows how methods developed in the context of statistical physics can be used to analyze gray-scale texture synthesis procedures based on the probabilistic paradigm of Gibbs random fields (GRF). In particular, using the mean-field equations of the texture GRF, the existence of a bifurcation point indicating the presence of a phase transition in the textural pattern is shown. Using simulations, it is shown that a number of interesting phenomena occur at the bifurcation temperature like a sudden decrease in energy, sharp peaks in similarity measures between textural patterns, and sudden saturation of the mean-field variables. For texture synthesis, it is sufficient to simulate the mean-field equations near the bifurcation temperature.

Citation Download Citation

Ibrahim M. Elfadel and Alan L. Yuille "Mean-field theory for grayscale texture synthesis using Gibbs random fields", Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); https://doi.org/10.1117/12.48383

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