Stochastic Fractal Models for Image Processing

Abstract : Our study of fractal landscapes departs from the simplest but yet effective model of fractional Brownian motion and explores its two-dimensional (2-D) extensions. We focus on the ability to introduce anisotropy in this model, and we are also interested in considering its discrete-space counterparts. We then move towards other multifractional and multifractal models providing more degrees of freedom for fitting complex 2-D fields. We note that many of the models and processing are implemented in FracLab, a software MATLAB/Scilab toolbox for fractal processing of signals and images.
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Article dans une revue
IEEE Signal Procesing Magazine, IEEE, 2002, 19 (5), pp.48-62. 〈10.1109/MSP.2002.1028352〉
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Beatrice Pesquet-Popescu, Jacques Lévy Véhel. Stochastic Fractal Models for Image Processing. IEEE Signal Procesing Magazine, IEEE, 2002, 19 (5), pp.48-62. 〈10.1109/MSP.2002.1028352〉. 〈inria-00581030〉

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