Salt and pepper noise reduction and edge detection algorithm based on neutrosophic logic

Abstract

Noise reduction of images is a challenging task in image processing. Salt and pepper noise is one kind of noise that affects a gray-scale image significantly. Generally, the median filter is used to reduce salt and pepper noise; it gives optimum results while compared to other image Filters. Median filter works only up to a certain level of noise intensity. Here we proposed a neighborhood-based image filter called nbd-filter, it works perfectly for gray image regardless of noise intensity. It reduces salt and pepper noise signficantly at any noise level and produces a noise-free image. Further, we proposed an edge detection algorithm based on the neutrosophic set, it detects edges efficiently for images corrupted by noise and noise-free images. Neutrosophic set (NS) is a powerful tool to deal with indeterminacy. Since most of the real-life images consists of indeterminate regions, Neutrosophy is a perfect tool for edge detection. In this paper, the neutrosophic set is applied to the image domain and a novel edge detection technique is proposed.