DocumentCode :
3376802
Title :
A Geometric Mean Based Adaptive Local Noise Removal Algorithm
Author :
Qiaoping, Sun ; Xiaoming, Zhao
Author_Institution :
Dept. of Comput., Taizhou Univ., Taizhou
fYear :
2005
fDate :
21-24 Nov. 2005
Firstpage :
1
Lastpage :
4
Abstract :
Adaptive filters are important application in the signal processing field. This paper discusses the adaptive local noise removal algorithm proposed by Professor Rafael C. Gonzalez and points out its shortcomings. To improve the algorithm, a new method, geometric mean based adaptive local noise removal algorithm, has been proposed. The simulation results indicate that the new algorithm is more satisfactory. The mean square error lscrmse is reduced by 1/4. The signals to noise ratios (i.e., SNR, SNRm, PSRN) are raised by 1/10.This algorithm has been shown promise for applications.
Keywords :
adaptive filters; mean square error methods; signal denoising; adaptive filters; adaptive local noise removal algorithm; geometric mean; mean square error; signal processing; signal to noise ratios; Adaptive filters; Additive noise; Filtering theory; Image denoising; Interference suppression; Nonlinear filters; Pixel; Signal processing algorithms; Signal to noise ratio; Wiener filter; Adaptive filtering; Geometric mean; Image de-noising; Local noise removal;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON 2005 2005 IEEE Region 10
Conference_Location :
Melbourne, Qld.
Print_ISBN :
0-7803-9311-2
Electronic_ISBN :
0-7803-9312-0
Type :
conf
DOI :
10.1109/TENCON.2005.300955
Filename :
4084919
Link To Document :
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