Comparative Analysis on Median Filter Categories for Accurate Noise Removal

The study of how to filter out noise in images is gaining popularity in the field of image processing. Images may become distorted because of a shift in pixels, a change in lighting, or a lack of contrast, rendering them useless. For this reason, eliminating impulse noise is a crucial step in any image processing workflow. Image details are obscured by noise. In order to improve image quality, it is essential to filter out background noise without damaging the original data. Preprocessing in image editing often includes removing noise. Filters based on the median are commonly used to get rid of noise at such high frequencies. In this analysis, we compare the effectiveness of the standard median filter, median filtering filters, and trying to switch adaptive median filters at eradicating noise from digital images. Finally, we provide a comprehensive comparison of these algorithms and discuss many exciting avenues for further study. The effectiveness of SSIM and PSNR was tested and evaluated extensively.