A simulator to aid in the design of nonlinear image processing filters
is developed. This simulator assists the filter design by determining
parameters manually by trial-and-error. The method is also useful for
improving the results of the learning optimization methods. An exampl
e of the application of the technique to improve a resultant filter by
a learning method of a mathematical morphological filter is shown.