On the Weighted Arithmetic Mean Fuzzy Filter
Manuel González-Hidalgo, Sebastià Massanet, Arnau Mir, Daniel Ruiz-Aguilera · 2015
Noise reduction is a fundamental step in many image processing and computer vision applications. In recent years, several noise filters especially devoted to the removal of high density salt and pepper noise, as a particular case of impulse noise, have been proposed. In this paper, a novel two-stage filter based on the fuzzy mathematical morphology using t-norms and aggregation functions is proposed. This filter involves a detection step of the noisy pixels and the restoration of the image by means of the aggregation of the non-corrupted pixels through an adequate weighted arithmetic mean. The experimental results show that the proposed algorithm outperforms other filtering methods both from the visual point of view and the values of some objective performance measures for images corrupted from a 25% up to 98% of noise.