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Data analytic wavelet threshold selection in 2-D signal denoising

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2 Author(s)
Hilton, M.L. ; Dept. of Comput. Sci., South Carolina Univ., Columbia, SC, USA ; Ogden, R.T.

A data adaptive scheme for wavelet shrinkage-based noise removal is developed. The method involves a statistical test of hypotheses that takes into account the wavelet coefficients' magnitudes and relative positions. The amount of smoothing performed during noise removal is controlled by the user-supplied confidence level of the tests

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Signal Processing, IEEE Transactions on  (Volume:45 ,  Issue: 2 )