Adaptive Wavelet Shrinkage For Image Denoising Based On SURE Rule

Author

Fei, Shuangbo ; Zhao, Ruizhen

Author_Institution

Inst. of Inf. Sci., Beijing Jiaotong Univ.

Volume

1

fYear

2006

fDate

16-20 2006

Abstract

Based on the wavelet shrinkage denoising theory proposed by D.L. Donoho, a new thresholding function is presented in this paper, which is rather similar to hard thresholding one. However it has infinite-order continuous derivative. Compared to soft thresholding function, it can reserve better image details due to its "hard" characteristic. Moreover, the new one makes it possible to construct an adaptive algorithm for image denoising. By using the new thresholding function, a new adaptive shrinkage method is presented based on Stein\´s unbiased risk estimate (SURE). The two examples Lenna and Barbara are given. The results indicted that for image denoising application, the proposed method is very effective in adaptively finding the optimal solution in the least mean square error (LMSE) sense

Keywords

image denoising; least mean squares methods; wavelet transforms; LMSE; SURE rule; Stein unbiased risk estimate; adaptive algorithm; adaptive wavelet shrinkage denoising theory; image denoising application; infinite-order continuous derivative; least mean square error; thresholding function; Continuous wavelet transforms; Image denoising; Image reconstruction; Information science; Mean square error methods; Noise level; Noise reduction; Optimization methods; Wavelet coefficients; Wavelet domain;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 2006 8th International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9736-3

Electronic_ISBN

0-7803-9736-3

Type

conf

DOI

10.1109/ICOSP.2006.344497

Filename

4128833