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Space-Frequency Localization as Bivariate Mother Wavelets Selecting Criterion for Hyperanalytic Bayesian Image Denoising

Domenii publicaţii > Stiinte ingineresti + Tipuri publicaţii > Articol în revistã ştiinţificã

Autori: Alexandru Isar

Editorial: World Scientific, Fluctuation and Noise Letters , Fluctuation and Noise Letters Vol. 11, No. 02, 2012.

Rezumat:

Throughout recent years, many Wavelet Transforms (WTs) were used in digital image processing: the Discrete WT (DWT), the Stationary WT (SWT) or the Hyperanalytic WT (HWT). All these transforms have in common a feature, the Mother Wavelets (MW) used. A great number of MWs was already proposed in literature. The purpose of this paper is the selection of the MW for hyperanalytic Bayesian image denoising on the basis of its space-frequency localization. The MW with the same space-frequency localization as the elements of the input image class gives the better results. Some procedures for the evaluation of the space-frequency localization of MWs and input images are proposed and applied to optimize the results obtained by the simulations of denoising, indicating the most appropriate MW.

Cuvinte cheie: fluctuatii, zgomot, interdisciplinaritate, stiinte fundamentale si aplicate // fluctuations, noise, interdisciplinary, fundamental and applied science

URL: http://www.worldscientific.com/worldscinet/fnl