Curvelet-based Model for the Generation of Anisotropic Fractional Brownian Fields

TL;DR

This paper introduces a curvelet-based method for generating anisotropic fractional Brownian fields, effectively modeling systems with orientation-dependent self-similarity, useful in geology, materials science, and complex media.

Contribution

The paper presents a novel curvelet-based synthesis approach for anisotropic fractional Brownian fields, capturing orientation-dependent correlations in natural stochastic systems.

Findings

Successfully models anisotropic systems with directional correlations

Generates fields with prescribed angular correlation distributions

Applicable to geological and material heterogeneity

Abstract

We propose a curvelet-based model for the generation of Anisotropic Fractional Brownian Fields, that are suited to model systems with orientation-dependent self-similar properties. The synthesis procedure consists of generating coefficients in the curvelet space with zero-mean Gaussian distribution. This approach allows the representation of natural systems having stochastic behavior in some degree and also obeying to a given angular distribution of correlations. Examples of such systems are found in heterogeneous geological structures, in anisotropic materials and in complex disordered media.