DocumentCode
2379597
Title
Correlated wavelet shrinkage: models of local random fields across multiple resolutions
Author
Azimifar, Z. ; Fieguth, P. ; Jernigan, E.
Author_Institution
Dept. of Syst. Design Eng., Waterloo Univ., Ont., Canada
Volume
3
fYear
2005
fDate
11-14 Sept. 2005
Abstract
This paper proposes a novel correlated shrinkage method based on wavelet joint statistics. Our objective is to demonstrate effectiveness of the wavelet correlation models [Z. Azimifar et al., 2004] in estimating the original signal from a noising observation. Simulation results are given to show the advantage of the new correlated shrinkage function. In comparison with the popular nonlinear shrinkage algorithms, it improves the denoised results.
Keywords
image denoising; image resolution; statistical analysis; wavelet transforms; correlated wavelet shrinkage; image denoising; image resolutions; local random fields; nonlinear shrinkage algorithms; wavelet correlation models; wavelet joint statistics; Additive noise; Bayesian methods; Design engineering; Hidden Markov models; Root mean square; Signal resolution; Statistics; Systems engineering and theory; Wavelet domain; Wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Print_ISBN
0-7803-9134-9
Type
conf
DOI
10.1109/ICIP.2005.1530352
Filename
1530352
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