IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

An Efficient Random Valued Impulse Noise Suppression Technique Using Artificial Neural Network and Non-Local Mean Filter

An Efficient Random Valued Impulse Noise Suppression Technique Using Artificial Neural Network and Non-Local Mean Filter
View Sample PDF
Author(s): Bibekananda Jena (Anil Neerukonda Institute of Technology & Sciences, Visakhapatnam, India), Punyaban Patel (Malla Reddy Institute of Technology, Secunderabad, India)and G.R. Sinha (CMR Technical Campus, Secunderabad, India)
Copyright: 2022
Pages: 17
Source title: Research Anthology on Artificial Neural Network Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-2408-7.ch055

Purchase


Abstract

A new technique for suppression of Random valued impulse noise from the contaminated digital image using Back Propagation Neural Network is proposed in this paper. The algorithms consist of two stages i.e. Detection of Impulse noise and Filtering of identified noisy pixels. To classify between noisy and non-noisy element present in the image a feed-forward neural network has been trained with well-known back propagation algorithm in the first stage. To make the detection method more accurate, Emphasis has been given on selection of proper input and generation of training patterns. The corrupted pixels are undergoing non-local mean filtering employed in the second stage. The effectiveness of the proposed technique is evaluated using well known standard digital images at different level of impulse noise. Experiments show that the method proposed here has excellent impulse noise suppression capability.

Related Content

Vinod Kumar, Himanshu Prajapati, Sasikala Ponnusamy. © 2023. 18 pages.
Sougatamoy Biswas. © 2023. 14 pages.
Ganga Devi S. V. S.. © 2023. 10 pages.
Gotam Singh Lalotra, Ashok Sharma, Barun Kumar Bhatti, Suresh Singh. © 2023. 15 pages.
Nimish Kumar, Himanshu Verma, Yogesh Kumar Sharma. © 2023. 16 pages.
R. Soujanya, Ravi Mohan Sharma, Manish Manish Maheshwari, Divya Prakash Shrivastava. © 2023. 12 pages.
Nimish Kumar, Himanshu Verma, Yogesh Kumar Sharma. © 2023. 22 pages.
Body Bottom