Title :
Data analytic wavelet threshold selection in 2-D signal denoising
Author :
Hilton, M.L. ; Ogden, R.T.
Author_Institution :
Dept. of Comput. Sci., South Carolina Univ., Columbia, SC, USA
fDate :
2/1/1997 12:00:00 AM
Abstract :
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
Keywords :
Gaussian noise; adaptive signal processing; image processing; interference suppression; smoothing methods; statistical analysis; wavelet transforms; white noise; 2D signal denoising; data adaptive scheme; data analytic wavelet threshold selection; hypotheses testing; smoothing; statistical test; user-supplied confidence level; wavelet shrinkage-based noise removal; Data analysis; Discrete wavelet transforms; Gaussian noise; Signal analysis; Signal denoising; Wavelet analysis; Wavelet coefficients; Wavelet domain; Wavelet transforms; White noise;
Journal_Title :
Signal Processing, IEEE Transactions on
