Cluster-based adaptive fuzzy switching median filter for universal impulse noise reduction

In this paper, we present a novel method for the removal of impulse noise from digital images. The proposed filter, called the Cluster-based Adaptive Fuzzy Switching Median (CAFSM), is composed of a cascaded easy-to- implement impulse detector and a detail preserving noise filter. Initially, the impulse detector classifies any possible impulsive noise pixels. Subsequently, the filtering phase replaces the detected noise pixels. In addition, the filtering phase employs fuzzy reasoning to deal with uncertainties present in local information. Contrary to many existing filters that only focus on a particular impulse noise model, the CAFSM filter is capable of filtering all kinds of impulse noise - the random-valued and/or fixed-valued impulse noise models. Extensive simulations conducted on 100 monochrome images under a wide range of noise densities show that the CAFSM filter substantially outperforms other state-of-the-art impulse noise filters. Furthermore, the relatively fast processing time suggests the CAFSM filter´s applicability in consumer electronic products such as digital cameras.