A Two-Pass Hybrid Mean and Median Framework for Eliminating Impulse Noise From a Grayscale Image
subject: Image Noise Cancellation; Image processing; Image Restoration; Salt and Pepper Noise; Visual quality
description: In a digital era, Image recuperation plays a vital role in the area of digital image processing. Image instauration offers more visualization on the quality of the image thereby eliminating noise. Elimination of Gaussian and impulse noise is a challenging problem in the area of image restoration. Rigorous research is pursued to restore salt-and-pepper (SAP) noise utilizing spatial filters. Mean and Median are two contributing spatial filters for eliminating impulse noise. This paper applies a two-pass hybrid mean and median framework on a corrupted grayscale image to replace salt and pepper noise. The hybrid framework is effectively restoring the image by abstracting the low, medium, and high-density impulse noise. The efficacy of the recommended strategy is evaluated by quantifying the peak signal to noise ratio and structural similarity index metric. The result obtained when compared with recent recuperation strategies outperforms to remove noise from grayscale images. 2021 IEEE
creator: Shiju Thomas M.Y.; Krishna A.V.N.
source: ACCESS 2021 - Proceedings of 2021 2nd International Conference on Advances in Computing, Communication, Embedded and Secure Systems, pp. 206-210.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2021-01-01
rights: Restricted Access
relation: ISBN: 978-172817136-4
format: Online
language: English
type: Conference paper
coverage: Shiju Thomas M.Y., Department of Computer Science and Engineering, School of Engineering and Technology Christ (Deemed to be) University, Karnataka, Bangalore, India; Krishna A.V.N., Department of Computer Science and Engineering, School of Engineering and Technology Christ (Deemed to be) University, Karnataka, Bangalore, India