Fuzzy rule-based signal processing and its application to image restoration

A novel signal processing technique based on fuzzy rules is proposed for estimating nonstationary signals, such as image signals, contaminated with additive random noises. In this filter, fuzzy rules concerning the relationship between signal characteristics and filter design are utilized to set the filter parameters, taking the local characteristics of the signal into consideration. The fuzzy rules are found to be quite effective, since the rules to set the filter parameters are usually expressed in an ambiguous style. The high performance of this filter is demonstrated in noise reduction of a 1-D test signal and a natural image with various training signals.<
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