Efficient adaptive fuzzy-based switching weighted average filter for the restoration of impulse corrupted digital images

This study proposes a new fuzzy adaptive filter for the restoration of impulse corrupted digital images. The proposed filter incorporates fuzzy functions to model the uncertainties, while detecting and correcting impulses. The traditional, SMALL fuzzy function is used to identify the non-impulsive nature of the detected corrupted pixels in the initial step. For the better restoration of detected impulsive pixels, a modified version of Gaussian function is utilised to determine the similarity among the detected uncorrupted pixels. The proposed correction scheme provides more weight to the uncorrupted pixels that show much similarity with other uncorrupted pixels in the window while replacing impulses. The proposed filter adapts to various noisy and image conditions and is capable of suppressing noise while preserving image details. The experimental results in terms of subjective and objective metrics favour the proposed algorithm than many other prominent filters in literature.