Bayesian multifractal signal denoising - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2003

Bayesian multifractal signal denoising

Abstract

This work presents an approach for signal/image denoising in a semi-parametric frame. Our model is a wavelet-based one, which essentially assumes a minimal local regularity. This assumption translates into constraints on the multifractal spectrum of the signals. Such constraints are in turn used in a Bayesian framework to estimate the wavelet coefficients of the original signal from the noisy ones. Our scheme is well adapted to the processing of irregular signals, such as (multi-)fractal ones, and is potentially useful for the processing of e.g. turbulence, bio-medical or seismic data.
Fichier principal
Vignette du fichier
Bayesian-multifractal-signal-denoising.pdf (161.29 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

inria-00576482 , version 1 (15-03-2011)

Identifiers

  • HAL Id : inria-00576482 , version 1

Cite

Jacques Lévy Véhel, Pierrick Legrand. Bayesian multifractal signal denoising. ICASSP03, IEEE International Conference on Acoustics, Speech, and Signal Processing, Apr 2003, Hong-Kong, China. ⟨inria-00576482⟩
187 View
324 Download

Share

Gmail Facebook X LinkedIn More