Description
Title: NEUTROSOPHIC LOGIC BASED SALT AND PEPPER NOISE REDUCTION AND EDGE DETECTION ALGORITHM
Abstract: The difficult task of image processing is image noise reduction. One type of noise that significantly affects the appearance of a grayscale image is salt and pepper noise. When compared to other image liters, the median liter produces the best results when used to reduce salt and pepper noise. Only a certain amount of noise intensity is tolerated by the median liter. The neighborhood-based image lter we proposed here, known as the nbd- lter, performs flawlessly for gray images regardless of noise intensity. It generates a noise-free image and significantly lowers salt and pepper noise at all noise levels. Additionally, we put forth an edge detection algorithm based on the neutrosophic set that efficiently detects edges in both noise-corrupted and noise-free images. The neutrosophic set (NS) is a potent tool for handling uncertainty. Neutrosophy is an ideal tool for edge detection because most real-world images contain regions of uncertainty. This study proposes a novel edge detection method and applies the neutrosophic set to the image domain.
Keywords: neutrosophic set, digital image processing, image analysis, image denoising, edge detection
Paper Quality: SCOPUS / Web of Science Level Research Paper
Paper type: Analysis Based Research Paper
Subject: Computer Science
Writer Experience: 20+ Years
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