Title :
Implementation of fuzzy cluster filter for nonlinear signal and image processing
Author :
Doroodchi, Mahmood ; Reza, Ali M.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Wisconsin Univ., Milwaukee, WI, USA
Abstract :
A nonlinear filter known as fuzzy cluster filter (FCF) is introduced. This filter can be used for different signal and image processing applications. The formulation of this filter is based on applying fuzzy clustering to a subset of the signal (or image) and finding the best candidate (i.e., the cluster prototype) for the output. The local statistics of the signal are used for learning the membership functions. Also, the performance of the filter is found for different signal to noise ratios (SNR) by using Monte Carlo simulations
Keywords :
Monte Carlo methods; filtering theory; fuzzy set theory; image processing; Monte Carlo simulations; best candidate; cluster prototype; fuzzy cluster filter; local statistics; membership functions; nonlinear signal processing; Application software; Fuzzy sets; Image processing; Image segmentation; Nonlinear filters; Prototypes; Signal processing; Signal to noise ratio; Statistics; Synthetic aperture radar;
Conference_Titel :
Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-3645-3
DOI :
10.1109/FUZZY.1996.552789
