An Adaptive Wavelet Shrinkage and its Application in Image De-Noising

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In this paper an adaptive method of shrinkage of the wavelet coefficients is presented. In the method, the wavelet coefficients are divided into two classes by a threshold. One class of them with the smaller absolute values at a scale is transformed with a proportional relation,another class with the larger absolute values at the same scale is transformed with a linear function. The threshold and the coefficient in the proportional relation or in the linear function are determined by the principle of minimizing the Stein’s unbiased risk estimate. In the paper, the method of estimation of the threshold and the coefficient is given and the adaptive method of shrinkage of the wavelet coefficients is applied to image denoising. Examples in the paper show that the presented method has an advantage over SureShrink from the point of view of both the Stein’s unbiased risk estimate and the signal-to-noise ratio. In addition, the method takes almost the same computing time as the SureShrink in image denoising.

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Periodical:

Edited by:

Zhixiang Hou

Pages:

500-503

DOI:

10.4028/www.scientific.net/AMM.128-129.500

Citation:

T. J. Cao "An Adaptive Wavelet Shrinkage and its Application in Image De-Noising", Applied Mechanics and Materials, Vols. 128-129, pp. 500-503, 2012

Online since:

October 2011

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$35.00

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