A Generalized Neuro-Fuzzy Filter for Removing Different Types of Noise in Digital Images by A Single Operator

In this work, a neuro-fuzzy based method intended for the removal of different types of noise in digital images by a single operator is proposed. It is demonstrated that a single operator can be used for the removal of different types of noise by creating suitable data sets. Performance of the proposed method is compared with the performances of the operators which are customized for different noise types. It is shown that the proposed method can be used as an efficient and simple tool for removing noise from digital images