Image Denoising Method Relying on Iterative Adaptive Weight-Mean Filtering

Salt-and-pepper noise (SPN) is a common type of image that appears as randomly distributed white and black pixels in an image. It also known impulse or random noise. This paper aims to introduce new weighted average based on the Atangana–Baleanu fractional integral operator, which well-known idea calculus. Our proposed method incorporates concept symmetry window mask structures, resulting efficient easily implementable filters for real-time applications. The distinguishing point these techniques compared similar methods we employ novel calculating mean regular rather than existing used formula along with median. An iterative procedure has been provided integrate power removing high-density Moreover, will explore different approaches denoising their effectiveness from images. symmetrical structure this tool help ease efficiency techniques. outputs are terms peak signal-to-noise ratio, mean-square error structural similarity values. was found our methodologies outperform some methods. they boast several advantages over alternative techniques, including computational efficiency, ability eliminate while preserving features, applicability.