Evolutionary Denoising Based on an Estimation of Hölder Exponents with Oscillations | Zendy

Pierrick Legrand | Zendy; Évelyne Lutton | Zendy; Gustavo Olague | Zendy

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Evolutionary Denoising Based on an Estimation of Hölder Exponents with Oscillations

Author(s) -

Pierrick Legrand,

Évelyne Lutton,

Gustavo Olague

Publication year - 2006

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-33237-5

DOI - 10.1007/11732242_49

Subject(s) - multifractal system , computer science , noise reduction , wavelet , noise (video) , exponent , signal (programming language) , algorithm , inverse , mathematics , artificial intelligence , pattern recognition (psychology) , mathematical analysis , fractal , linguistics , philosophy , geometry , image (mathematics) , programming language

International audienceIn multifractal denoising techniques, the acuracy of the Holder 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 H¨older 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 whichis 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 [J. Levy Vehel and E. Lutton, "Evolutionary signal enhancement based on holder regularity analysis," EVOIASP2001, LNCS 2038, 2001.], which necessitates the design of ad-hoc genetic operators

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