Adaptive weighted median filters by using fuzzy techniques

In this paper, we propose adaptive weighted median (AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by fuzzy rules (fuzzy weighted median: FWM filters). By using the rule-based fuzzy techniques, the better weights are easily derived. Experimental results show AWM filters can suppress nonimpulsive and impulsive noise, while preserving signal details.