DocumentCode
1288848
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
Volume
45
Issue
2
fYear
1997
fDate
2/1/1997 12:00:00 AM
Firstpage
496
Lastpage
500
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;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.554318
Filename
554318
Link To Document