A comparative analysis of image denoising filters
Jiahui Shen, Qiming Huang, Zihao Ding, Jinfen Liu · 2025
Noise reduction is a perplexing task for digital image processing researchers. However, high quality images have become an urgent need in various fields of today's society. In this paper, we demonstrate the denoising performance of median filter, mean filter, wiener filter and gaussian filter on gray and binary images with gaussian, salt and pepper and speckle noise. After comparing and analyzing the numerical results, we find that the median filter performs better in denoising grayscale images in low-density environments with salt and pepper noise, the wiener and mean filters perform best in mitigating gray image noise in environments with speckle noise. In practical applications, image denoising can remove redundant and interfering information and ensure the correct expression of information, thus significantly improving the image quality and laying a good foundation for subsequent advanced image processing tasks. It can be seen that analyzing the advantages and scope of application of different denoising algorithms is of great significance for practical applications.