Title :
Multiwavelets denoising using neighboring coefficients
Author :
Chen, G.Y. ; Bui, T.D.
Author_Institution :
Dept. of Comput. Sci., Concordia Univ., Montreal, Canada
fDate :
7/1/2003 12:00:00 AM
Abstract :
Multiwavelets give better results than single wavelets for signal denoising. We study multiwavelet thresholding by incorporating neighboring coefficients. Experimental results show that this approach is better than the conventional approach, which only uses the term-by-term multiwavelet denoising. Also, it outperforms neighbor single wavelet denoising for some standard test signals and real-life images. This is an extension to Cai and Silverman´s (see Sankhya: Ind. J. Stat. B, pt.2, vol.63, p.127-148, 2001) work.
Keywords :
image denoising; wavelet transforms; multiwavelet thresholding; multiwavelets denoising; neighbor single wavelet denoising; neighboring coefficients; real-life images; signal denoising; standard test signals; Gaussian distribution; Hidden Markov models; Higher order statistics; Noise reduction; Signal denoising; Testing; Wavelet coefficients; Wavelet domain; Wavelet transforms; White noise;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2003.811586