MORPHOLOGICAL FILTERS USING SIMULATED ANNEALING TECHNIQUE

Abstract Nonlinear filters are becoming an increasingly popular area of image and signal processing. They are often better than linear filters in removing noise without distorting image features. Among these nonlinear filters, morphological filters are one of the most important and useful, providing an important class of image and signal processing operators. Another well-known class of non-linear filters is the class of rank order filters. Soft morphological filters are a combination of morphological and weighted rank order filters. Soft morphological filters improve the behavior of standard morphological filters in noisy conditions. But design methods existing for these filters tend to be computationally intractable or require some special knowledge. Heuristic based approach- Simulated annealing provide a useful tool for the design and optimization of soft morphological filters. In this paper, a new method for the soft morphological filter design using simulated annealing is proposed and illustrated by empirical results. It is found that the performance of the filter is better under MSE error criterion than MAE criterion.