Abstract
We describe a probabilistic model representing piecewise-homogeneous digital (raster) gray- scale textured images as samples of certain Markov random field with short- and long-range pairwise interactions between the signals (gray-scale levels and labels of homogeneous regions) in the pixels. The model is given by a Gibbs probability distribution specified by a sum of terms which gives a total strength of the interaction. Each term defines the probability of the signal values in a pixel or a pair of the pixels in superim-posed image and region map. Unknown parameters of the model can be estimated by using a stochastic approximation technique. Several results in generating and segmenting the textured images are presented.
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References
D.S.Lebedev, A.A.Bezruk, V.M.Novikov: Markov probabilistic model of image and picture. Preprint Inst. of Information Transmission Problems, Acad. of Sciences of the USSR. Moscow: VINITI 1983, 40 p. (In Russian)
HDerin, H.Elliott, R.Cristi, D.Geman: Bayes smoothing algorithms for segmentation of binary images modelled by Markov random fields. IEEE Trans. on Pattern Anal. and Machine Intell. 6(6), 707–720 (1984)
S Geman, D.Geman: Stochastic relaxation, Gibbs distributions, and bayesian restoration of images. Ibid., 721–741.
H Derin, W.S.Cole: Segmentation of textured images using Gibbs random fields. Computer Vision, Graphics, and Image Processing, 35(1), 72–98 (1986)
J Marroquin, S.Mitter, T.Poggio: Probabilistic solution of illposed problems in computational vision. J. of the Amer. Stat. Assoc. 82(397), 76–89 (1987)
G.L.Gimel'farb, A.V.Zalesny: Models of Markov random fields in the problems of generating and segmenting textured images. In: Means to Intellectualize Cybernetic Systems. V.M.Glushkov Inst. of Cybernetics. Acad. of Sciences of the Ukrainian SSR. Kiev: 1989, pp.27–36. (In Russian)
G.L.Gimel'farb, A.V.Zalesny: Low-level Bayesian segmentation of piecewise-homogeneous noisy and textured images. Int. J. of Imaging Systems and Technology 3(3),227–243 (1991)
G.L.Gimel'farb, A.V.Zalesny: Gibbs random fields as generating models of textured region maps. In: Proc. of the First All-Ukrainian Conf. on Signal/Image Processing and Pattern Recognition (UkrOBRAZ'92), Ukraine, Kyjiv, Nov. 17–21, 1992. Kijiv: Inst.of Cybernetics 1992, pp.62–64. (In Ukrainian)
G.L.Gimel'farb A.V.Zalesny: Probabilistic models of digital region maps on the basis of Markov fields with short-and long-range interaction. In: Theoretical and Applied Questions of Image Recognition. V.M.Glushkov Inst. of Cybernetics. Acad. of Sciences of Ukraine. Kiev: 1992, pp.5–15. (In Russian)
A.V.Zalesny, V.N.Yushakov: Experiments in image generation. Ibid.In:, pp.15–26. (In Russian)
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© 1993 Springer-Verlag Berlin Heidelberg
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Gimel'farb, G.L., Zalesny, A.V. (1993). Markov random fields with short- and long-range interaction for modelling gray-scale textured images. In: Chetverikov, D., Kropatsch, W.G. (eds) Computer Analysis of Images and Patterns. CAIP 1993. Lecture Notes in Computer Science, vol 719. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57233-3_37
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DOI: https://doi.org/10.1007/3-540-57233-3_37
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