p-exponent and p-leaders, Part I: Negative pointwise regularity
Multifractal analysis aims to characterize signals, functions, images or fields, via the
fluctuations of their local regularity along time or space, hence capturing crucial features of …
fluctuations of their local regularity along time or space, hence capturing crucial features of …
p-exponent and p-leaders, Part II: Multifractal analysis. Relations to detrended fluctuation analysis
Multifractal analysis studies signals, functions, images or fields via the fluctuations of their
local regularity along time or space, which capture crucial features of their temporal/spatial …
local regularity along time or space, which capture crucial features of their temporal/spatial …
A Bayesian framework for multivariate multifractal analysis
Multifractal analysis has become a reference tool for signal and image processing.
Grounded in the quantification of local regularity fluctuations, it has proven useful in an …
Grounded in the quantification of local regularity fluctuations, it has proven useful in an …
A review of univariate and multivariate multifractal analysis illustrated by the analysis of marathon runners physiological data
We review the central results concerning wavelet methods in multifractal analysis, which
consists in analysis of the pointwise singularities of a signal, and we describe its recent …
consists in analysis of the pointwise singularities of a signal, and we describe its recent …
Multifractal analysis of multivariate images using gamma Markov random field priors
Texture characterization of natural images using the mathematical framework of multifractal
analysis (MFA) enables the study of the fluctuations in the regularity of image intensity …
analysis (MFA) enables the study of the fluctuations in the regularity of image intensity …
Bayesian estimation of the multifractality parameter for image texture using a Whittle approximation
S Combrexelle, H Wendt, N Dobigeon… - … on Image Processing, 2015 - ieeexplore.ieee.org
Texture characterization is a central element in many image processing applications.
Multifractal analysis is a useful signal and image processing tool, yet, the accurate …
Multifractal analysis is a useful signal and image processing tool, yet, the accurate …
Multifractality and long-range dependence of asset returns: the scaling behavior of the Markov-switching multifractal model with lognormal volatility components
In this paper, we consider daily financial data from various sources (stock market indices,
foreign exchange rates and bonds) and analyze their multiscaling properties by estimating …
foreign exchange rates and bonds) and analyze their multiscaling properties by estimating …
Assessing cross-dependencies using bivariate multifractal analysis
Multifractal analysis, notably with its recent wavelet-leader based formulation, has nowadays
become a reference tool to characterize scale-free temporal dynamics in time series. It …
become a reference tool to characterize scale-free temporal dynamics in time series. It …
Bayesian estimation of the parameters of the bivariate multifractal spectrum
Multifractal analysis is a reference tool for the analysis of data based on local regularity and
has proven useful in an increasing number of applications involving univariate data (scalar …
has proven useful in an increasing number of applications involving univariate data (scalar …
Multifractal characterization for bivariate data
Multifractal analysis is a reference tool for the analysis of data based on local regularity,
which has been proven useful in an increasing number of applications. However, in its …
which has been proven useful in an increasing number of applications. However, in its …