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Multifractal analysis is considered a promising tool for image processing, notably for texture characterization. However, practical operational estimation procedures based on a theoretically well established multifractal analysis are still lacking for image (as opposed to signal) processing. In the present contribution , a wavelet Leader based multifractal(More)
— Classical within-subject analysis in functional Magnetic Resonance Imaging (fMRI) relies on a detection step to localize which parts of the brain are activated by a given stimulus type. This is usually achieved using model-based approaches. Here, we propose an alternative exploratory analysis. The originality of this contribution is twofold. First, we(More)
B. Mandelbrot gave a new birth to the notions of scale invariance, selfsimilarity and non-integer dimensions, gathering them as the founding cornerstones used to build up frac-tal geometry. The first purpose of the present contribution is to review and relate together these key notions, explore their interplay and show that they are different facets of a(More)
A priori discrimination of high mortality risk amongst congestive heart failure patients constitutes an important clinical stake in cardiology and involves challenging analyses of the temporal dynamics of heart rate variability (HRV). The present contribution investigates the potential of a new multifractal formalism, constructed on wavelet p-leader(More)
Scale invariance is a widely used concept to analyze real-world data from many different applications and multifractal analysis has become the standard corresponding signal processing tool. It characterizes data by describing globally and geometrically the fluctuations of local regularity, usually measured by means of the Hölder exponent. A major limitation(More)
Multifractal analysis, that mostly consists of measuring scaling exponents, is becoming a standard technique available in most empirical data analysis toolboxes. Making use of the most recent theoretical results, it is based here on the estimation of the cumulants of the log of the wavelet Leaders, an elaboration on the wavelet coefficients. These(More)
— Interpretation and analysis of intrapartum fetal heart rate, enabling early detection of fetal acidosis, remains a challenging signal processing task. Recently, a variant of the wavelet-based multifractal analysis, based on p p p-exponents and p p p-leaders, which provides a rich framework for data regularity analysis, has been proposed. The present(More)
Recently, a growing interest has emerged for examining the potential of Image Processing tools to assist Art Investigation. Simultaneously, several research works showed the interest of using multifractal analysis for the description of homogeneous textures in images. In this context, the goal of the present contribution is to study the benefits of using(More)
Image classification often relies on texture characterization. Yet texture characterization has so far rarely been based on a true 2D multifractal analysis. Recently, a 2D wavelet Leader based multifractal formalism has been proposed. It allows to perform an accurate, complete and low computational and memory costs multifractal characterization of textures(More)