Adaptive weighted median filters by using fuzzy techniques
Misaki Meguro, Akira Taguchi · 2002
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.