Optimization of soft-morphological filters by genetic algorithms

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Abstract
In this work we present a new approach to robust image modeling. the proposed method is based on M-estimation algorithms. However, unlike in other M-estimator based image processing algorithms, the new algorithm takes into consideration spatial relations between picture elements. The contribution of the sample to the model depends not only on the current residual of that sample, but also on the neighboring residuals. In order to test the proposed algorithm we apply it to an image filtering problem, where images are modeled as piecewise polynomials. We show that the filter based on our algorithm has excellent detail preserving properties while suppressing additive Gaussian and impulsive noise very efficiently.

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