DocumentCode
3640869
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
Volume
2
fYear
2002
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"
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing (ICASSP), 2002 IEEE International Conference on
ISSN
1520-6149
Print_ISBN
0-7803-7402-9
Type
conf
DOI
10.1109/ICASSP.2002.5744031
Filename
5744031
Link To Document