An effective method for salt and pepper noise removal based on algebra and fuzzy logic function

Image denoising techniques are very important in modern digital image processing. Many classical denoising algorithms have evolved over the years, such as Butterworth filter, Mean filter, Median filter, Laplacian filter, Multidimensional filter, Gaussian filter and Wiener filter. In this paper, a new method of removing high density salt and pepper noise is proposed via using Lukasicwicz algebra with square root (MV-algebra) and fuzzy logic function for digital images. In the proposed method, a new constructed fuzzy logic function in MV-algebra is used to remove the salt and pepper noise in contaminated images. The proposed method is called LASRNM, which has a strong mathematical foundation and strong robustness in removing salt and pepper noise. Therefore, experiments on five datasets illustrate that our proposed LASRNM method works the best in high density salt and pepper noise situation in terms of the peak signal noise ratio (PSNR), signal to noise ratio (SNR) and structural similarity (SSIM).