By using a fuzzy metric-like space \((\mathbb {FMLS})\) to redefine the idea of peer group, this study offers a novel chromatic filtering technique for removing outliers. The technique uses features of \(\mathbb {FML}\) space to enable effective corrupted pixel detection. The suggested filtering method is intended to preserve fine image features while successfully restoring color images that have been deteriorated by excessive amounts of impulsive noise. Additionally, a switching technique is shown that, based on the results of noisy pixel detection, intelligently switches between the identification operation and Enhanced Average Filtering Technique.
