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
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;
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
DOI :
10.1109/CCDC.2009.5195268