Multifractal analysis has matured into a widely used signal and image processing tool. Due
to the statistical nature of multifractal processes (strongly non-Gaussian and intricate …

Multifractal analysis is a powerful tool used in signal processing. Multifractal models are
essentially characterized by two parameters, the multifractality parameter c 2 and the …

Multifractal analysis is nowadays commonly used in real-life data analyses and involved in
standard signal processing tasks such as detection, identification or classification. In a …

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 …

Multifractal analysis has become a powerful signal processing tool that characterizes signals
or images via the fluctuations of their pointwise regularity, quantified theoretically by the so …

Texture analysis is an image processing task that can be conducted using the mathematical
framework of multifractal analysis to study the regularity fluctuations of image intensity and …

Multifractal analysis provides the theoretical and practical tools for describing the
fluctuations of pointwise regularity in data and has led to many successful applications in …

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 …

Multifractal analysis, which mainly consists in estimating scaling exponents, has become a
popular tool for empirical data analysis. Although widely used in different applications, the …

We introduce a new multifractal formalism based on wavelet leaders and study its
properties. Comparing it against previously formulated wavelet coefficient based multifractal …