Title :
Adaptive weighted fuzzy mean filter
Author :
Lee, Chang-Shing ; Kuo, Yau-Hwang
Author_Institution :
Inst. of Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Abstract :
A new fuzzy filter for the removal of additive impulse noise, called the adaptive weighted fuzzy mean (AWFM) filter, is proposed and analyzed in this paper. The AWFM is an extensive version of weighted fuzzy mean (WFM) filter and its filtered output signal is either the output of WFM or the processed signal by the detection algorithm. This filter gives very superior performance compared with conventional filters when evaluated by mean absolute error (MAE), mean square error (MSE) and subjective evaluation criteria. For dedicated hardware implementation, AWFM is also much simpler than the conventional median filter
Keywords :
adaptive filters; fuzzy set theory; image processing; noise; adaptive weighted fuzzy mean filter; additive impulse noise; detection algorithm; mean absolute error; mean square error; subjective evaluation criteria; Adaptive filters; Delta modulation; Design methodology; Digital images; Fuzzy sets; Hardware; Histograms; Noise level; Pixel; Sorting;
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.1996.552788
