SYNTHESIS OF FUZZY CENTER WEIGHTED MEDIAN FILTERS

Nonlinear filters are known to be effective for restoration of image s ignals subject to additive noise. Among them, the most typical are med ian filters, and particularly popular are stack filters. Signal proces sing in the stack filters involves the following three stages: thresho ld value decomposition, calculation of the Boolean function output at each level, and signal synthesis. The Boolean function is defined by t he binary input/output. However, to achieve better filter characterist ics and design diversity, the authors considered using fuzzy Boolean f unctions defined by continuous output values from 0 to 1, rather than conventional Boolean functions. In the current study, the authors perf ormed fuzzification of such common stack filters as the median filter and center weighted median (CWM) filter. Fuzzification was performed b y using fuzzy Boolean functions to define the median filter or the CWM filter. The fuzzy Boolean function is derived from fuzzy inference. A s a next step, the authors developed a method for fuzzy inference opti mization (tuning method). (C) 1998 Scripta Technica.