Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density

Many computer vision algorithms which are not robust to noise incorporate a removal stage in their workflow avoid distortions the final result. In last decade, many filters for salt-and-pepper have been proposed. this paper, novel filter based on weighted arithmetic mean aggregation function and fuzzy mathematical morphology is The performance of proposed highly competitive when compared with other state-of-the-art regardless amount present image, achieving notable results any density from 5% 98%. A statistical analysis some objective restoration measures supports that surpasses several most levels considered comparison experiments.