A SELF-DUAL FILTERING TOGGLE OPERATOR FOR SPECKLE NOISE FILTERING

Abstract

In this work, we formalize an alternative way to build self-dual morphological filters that extends some results obtained for morphological centers to a different class of toggle operators. Thus, a wider range of primitives can be considered without causing oscillations, a common problem in toggle mappings. We also show that the combination of the morphological filters generated by using the proposed approach with the well-known anisotropic diffusion technique yields sound results where homogeneous regions are smoothed without degrading edge information. We explore the filtering of speckle noise, an interference pattern that causes a granular aspect in the image, thus limiting its interpretation and making it difficult further image processing tasks. Experimental tests on both synthetic and real-world images show promising results when compared to some well-known methods related to this type of filtering.