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Model Fitting and Model Evidence for Multiscale Image Texture Analysis
2004
AIP Conference Proceedings
This paper, begins with an overview of the two levels of Bayesian inference: model fitting and model selection, and shows how they can be used for the image texture analysis. The applied models are the Gauss-Markov and Gibbs auto-binomial Random Fields. In the second part the article introduces a linear model for the image wavelet coefficients able to explain the full description of the spatial, inter-scale and inter-band behavior of a multi-resolution decomposed image. The model parametrs,
doi:10.1063/1.1835195
fatcat:sfnmeqrr5zajxapfmioj4zwd7m