Impulsive Noise Suppression Methods Based on Time Adaptive Self-Organizing Map

Seyed Hamidreza Hazaveh, Ali Bayandour, Azam Khalili, Ali Barkhordary, Ali Farzamnia () and Ervin Gubin Moung
Additional contact information
Seyed Hamidreza Hazaveh: Faculty of Mechanical, Electrical Power and Computer, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran
Ali Bayandour: Ekbatan Higher Education Institute, Department of Electrical Engineering, Qazvin 3491915879, Iran
Azam Khalili: Department of Electrical Engineering, Malayer University, Malayer 6574184621, Iran
Ali Barkhordary: Expert of the Department of Industry and Community Relations, Malayer University, Malayer 6574184621, Iran
Ali Farzamnia: Faculty of Engineering, Universiti Malaysia Sabah, Kota Kinabalu 88400, Malaysia
Ervin Gubin Moung: Faculty of Computing and Informatics, Universiti Malaysia Sabah, Kota Kinabalu 88400, Malaysia

Energies, 2023, vol. 16, issue 4, 1-15

Abstract: Removal of noise and restoration of images has been one of the most interesting topics in the field of image processing in the past few years. Existing filter-based methods can remove image noise; however, they cannot preserve image quality and information such as lines and edges. In this article, various classifiers and spatial filters are combined to achieve desirable image restoration. Meanwhile, the time adaptive self-organizing map ( TASOM ) classifier is more emphasized in our feature extraction and dimensionality reduction approaches to preserve the details during the process, and restore the images from noise. The TASOM was compared with the self-organizing map ( SOM ) network, and a suitable noise reduction method for images was attempted. As a result, we achieved an optimum method to reduce impulsive noise. In addition, by using this neural network, better noise suppression was achieved. Experimental results show that the proposed method effectively removes impulse noise and maintains color information as well as image details.

Keywords: classification; time adaptive self-organizing map; impulsive noise; noise removal; noise suppression; neural networks; wavelet; spatial filters (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/4/2034/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/4/2034/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:4:p:2034-:d:1073174

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().