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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Seyed Hamidreza Hazaveh & Ali Bayandour & Azam Khalili & Ali Barkhordary & Ali Farzamnia & Ervin Gubin Moung, 2023. "Impulsive Noise Suppression Methods Based on Time Adaptive Self-Organizing Map," Energies, MDPI, vol. 16(4), pages 1-15, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:2034-:d:1073174
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    References listed on IDEAS

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    1. Ammar H. Elsheikh & Taher A. Shehabeldeen & Jianxin Zhou & Ezzat Showaib & Mohamed Abd Elaziz, 2021. "Prediction of laser cutting parameters for polymethylmethacrylate sheets using random vector functional link network integrated with equilibrium optimizer," Journal of Intelligent Manufacturing, Springer, vol. 32(5), pages 1377-1388, June.
    2. Mohamed Abd Elaziz & Mahmoud Ahmadein & Sabbah Ataya & Naser Alsaleh & Agostino Forestiero & Ammar H. Elsheikh, 2022. "A Quantum-Based Chameleon Swarm for Feature Selection," Mathematics, MDPI, vol. 10(19), pages 1-17, October.
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