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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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https://hal.inria.fr/inria-00581030
Contributor : Lisandro Fermin <>
Submitted on : Wednesday, March 30, 2011 - 8:14:02 AM
Last modification on : Monday, August 3, 2020 - 4:38:03 PM
Long-term archiving on: : Saturday, December 3, 2016 - 10:13:00 PM

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Beatrice Pesquet-Popescu, Jacques Lévy Véhel. Stochastic Fractal Models for Image Processing. IEEE Signal Processing Magazine, Institute of Electrical and Electronics Engineers, 2002, 19 (5), pp.48-62. ⟨10.1109/MSP.2002.1028352⟩. ⟨inria-00581030⟩

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