DocumentCode
461552
Title
Signal denoising via median filter & wavelet shrinkage based on heavy-tailed modeling
Author
Wei, Guang-Fen ; Jian, Tao ; Qiu, Rong-jian
Author_Institution
Dept. of Electron. Eng., Shandong Inst. of Bus. & Technol.
Volume
1
fYear
2006
fDate
16-20 2006
Abstract
Heavy-tailed noise has more outliers than Gaussian noise, and traditional wavelet threshold cannot suppress outliers. A new method combining wavelet threshold and median filter is proposed. After suppressing the outliers in signal through median filter, the wavelet threshold is applied and remained noise is removed further. The experimental error analysis shows that the new method can suppress heavy-tailed noise effectively, and it is more robust than classic wavelet threshold
Keywords
Gaussian noise; median filters; signal denoising; wavelet transforms; Gaussian noise; heavy-tailed modeling; median filter; signal denoising; wavelet shrinkage; Data mining; Error analysis; Filters; Gaussian distribution; Gaussian noise; Noise reduction; Noise robustness; Signal denoising; Wavelet analysis; White noise;
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.2006.344443
Filename
4128779
Link To Document