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
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;
Conference_Titel :
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Print_ISBN :
0-7803-9134-9
DOI :
10.1109/ICIP.2005.1530352
