DocumentCode
2845141
Title
Improved adaptive wavelet threshold for image denoising
Author
Zhang, Wei ; Yu, Fei ; Guo, Hong-mi
Author_Institution
Sch. of Autom. & Electron. Eng., Qingdao Univ. of Sci. & Technol., Qingdao, China
fYear
2009
fDate
17-19 June 2009
Firstpage
5958
Lastpage
5963
Abstract
Adaptive wavelet threshold for Bayes shrink (Bayes threshold) is a simple and effective method for image denoising. Multiple wavelet representations have excellent performance in image denoising. In this paper, combining the multiple wavelet representations with the Bayes threshold and using their advantages in image denoising, proposes a new image denoising algorithm which called M-Bayes threshold. It is simple and effective. Simulation results show that the proposed M-Bayes threshold can achieve the state-of-the-art image denoising performance at the low computational complexity.
Keywords
Bayes methods; computational complexity; image denoising; Bayes shrink; Bayes threshold; M-Bayes threshold; adaptive wavelet threshold; computational complexity; image denoising; Adaptive control; Automatic control; Automation; Computational modeling; Discrete wavelet transforms; Image denoising; Programmable control; Signal denoising; Signal processing algorithms; Wavelet coefficients; Adaptive wavelet threshold; Bayes shrink; Image denoising; Multiple wavelet representations;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location
Guilin
Print_ISBN
978-1-4244-2722-2
Electronic_ISBN
978-1-4244-2723-9
Type
conf
DOI
10.1109/CCDC.2009.5195268
Filename
5195268
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