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
Link To Document :
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