Title :
A bivariate shrinkage function for wavelet-based denoising
Author :
Levent Şendur;Ivan W. Selesnick
Author_Institution :
Electrical Engineering, Polytechnic University, 6 Metrotech Center, Brooklyn, NY 11201, USA
fDate :
5/1/2002 12:00:00 AM
Abstract :
Most simple nonlinear thresholding rules for wavelet-based denoising assume the wavelet coefficients are independent. However, wavelet coefficients of natural images have significant dependency. In this paper, a new heavy-tailed bivariate pdf is proposed to model the statistics of wavelet coefficients, and a simple nonlinear threshold function (shrinkage function) is derived from the pdf using Bayesian estimation theory. The new shrinkage function does not assume the independence of wavelet coefficients.
Keywords :
"Argon","Computational modeling","Noise measurement"
Conference_Titel :
Acoustics, Speech, and Signal Processing (ICASSP), 2002 IEEE International Conference on
Print_ISBN :
0-7803-7402-9
DOI :
10.1109/ICASSP.2002.5744031