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.