Title :
Fuzzy cluster filter
Author :
Doroodchi, Mahmood ; Reza, Ali M.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Wisconsin Univ., Milwaukee, WI, USA
Abstract :
A generalized nonlinear filter called the fuzzy cluster filter is introduced. This filter applies fuzzy clustering inside a running-window to estimate the clean output (i.e., geometrical center of the window). This filter is capable of cancelling the heavy-tailed contaminated Gaussian noise with a good performance. The results on some signals and images demonstrate the efficacy of this approach. The performance of the method is found by calculating the mean-square-error (MSE) for different signal-to-noise ratios using Monte Carlo simulations
Keywords :
Gaussian noise; Monte Carlo methods; digital filters; estimation theory; fuzzy set theory; image processing; interference suppression; nonlinear filters; Monte Carlo simulations; cancellation; clean output; fuzzy cluster filter; generalized nonlinear filter; geometrical center; heavy-tailed contaminated Gaussian noise; images; mean-square-error; performance; running-window; signal-to-noise ratios; signals; Adaptive filters; Filtering; Gaussian noise; Image segmentation; Magnetic separation; Medical simulation; Nonlinear filters; Prototypes; Signal processing; Signal to noise ratio;
Conference_Titel :
Image Processing, 1996. Proceedings., International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7803-3259-8
DOI :
10.1109/ICIP.1996.561059
