DocumentCode :
1883073
Title :
Parallelization of Fuzzy-Classical Filters For Image Noise Reduction
Author :
Vahdat-Nejad, H. ; Zolfaghari, H. ; Monsefi, R.
Author_Institution :
Islamic Azad Univ., Birjand
fYear :
2007
fDate :
27-29 June 2007
Firstpage :
25
Lastpage :
28
Abstract :
Several fuzzy filters for image noise reduction have already been developed. In general, they are able to preserve images in a more comprehensive means than classical filters, and they have the ability to combine edge-preservation and smoothing. However, the implementation of fuzzy filters is very time- consuming. On the other hand, parallel and grid computing technologies are efficient tools for implementing fuzzy filters. In this paper, we propose a parallel skeleton for some fuzzy weighted mean filters. We have implemented the algorithms using MatlabMPI (a parallel, message passing version of Matlab). Our experiments show the feasibility and efficiency of the algorithms.
Keywords :
adaptive filters; grid computing; image denoising; mathematics computing; smoothing methods; MatlabMPI; edge-preservation; edge-smoothing; fuzzy-classical filters parallelization; grid computing; image noise reduction; parallel computing; parallel skeleton; Application software; Computer languages; Concurrent computing; Filters; Grid computing; Message passing; Noise reduction; Parallel processing; Pixel; Skeleton; Parallel computing; fuzzy weighted mean filters; image processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Measurement Systems and Applications, 2007. CIMSA 2007. IEEE International Conference on
Conference_Location :
Ostuni
Print_ISBN :
978-1-4244-0823-8
Type :
conf
DOI :
10.1109/CIMSA.2007.4362532
Filename :
4362532
Link To Document :
بازگشت