Abstract

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 their temporal/spatial dynamics. Multifractal analysis is becoming a standard tool in signal and image processing, and is nowadays widely used in numerous applications of different natures. Its common formulation relies on the measure of local regularity via the Hölder exponent, by nature restricted to positive values, and thus to locally bounded functions or signals. It is here proposed to base the quantification of local regularity on pp-exponents, a novel local regularity measure potentially taking negative values. First, the theoretical properties of pp-exponents are studied in detail. Second, wavelet-based multiscale quantities, the pp-leaders, are constructed and shown to permit accurate practical estimation of pp-exponents. Exploiting the potential dependence with pp, it is also shown how the collection of pp-exponents enriches the classification of locally singular behaviors in functions, signals or images. The present contribution is complemented by a companion article developing the pp-leader based multifractal formalism associated to pp-exponents.

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