Evolutionary Denoising Based on an Estimation of Hölder Exponents with Oscillations

  • Pierrick Legrand
  • Evelyne Lutton
  • Gustavo Olague
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3907)


In multifractal denoising techniques, the acuracy of the Hölder exponents estimations is crucial for the quality of the outputs. In continuity with the method described in [1], where a wavelet decomposition was used, we investigate the use of another Hölder exponent estimation technique, based on the analysis of the local “oscillations” of the signal. The associated inverse problem to be solved, i.e. finding the signal which is the closest to the initial noisy one but having the prescribed regularity, is then more complex. Moreover, the associated search space is of a different nature as in [1], which necessitates the design of ad-hoc genetic operators.


Original Signal Noisy Signal Denoising Method Weierstrass Function Denoising Technique 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Pierrick Legrand
    • 1
    • 2
  • Evelyne Lutton
    • 2
  • Gustavo Olague
    • 1
  1. 1.CICESE, Research Center, Applied Physics DivisionCentro de Investigación Científica y de, Educación Superior de EnsenadaEnsenadaMéxico
  2. 2.INRIA RocquencourtComplex Team, Domaine de VoluceauLe ChesnayFrance

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