Low-density noise removal based on lambda multi-diagonal matrix filter for binary image

Abstract

Binary image denoising is a well-known problem, and it is the concern of diverse application areas. Many classical denoising techniques have evolved over the years, such as mean filter, median filter, and morphological filter. A new denoising method based on the multiplication of lambda multi-diagonal binary matrix (\(\lambda \)-MDBM) is proposed for binary images in this paper. In proposed method, first the users need to choose an appropriate lambda value from the set \(\{\lambda |\lambda \in [0.5,1]\}\), and then the hybrid noisy binary image matrix can be obtained by adding the noisy binary image matrix times the \(\lambda \)-MDBM and the transpose of the noisy binary image matrix times the \(\lambda \)-MDBM, and finally the de-noised binary image can be obtained by a preset threshold. The experimental results show that a new denoising method based on \(\lambda \)-MDBM is possible in peak signal-to-noise ratio and mean square error.