Abstract
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 example of the application of the technique to improve a resultant filter by a learning method of a mathematical morphological filter is shown.
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