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A New Neutrosophic Approach To Image Denoising

Author

Listed:
  • YANHUI GUO

    (School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China;
    Department of Computer Science, Utah State University, Logan, UT 84322, USA)

  • H. D. CHENG

    (School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China;
    Department of Computer Science, Utah State University, Logan, UT 84322, USA)

  • YINGTAO ZHANG

    (School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China)

Abstract

A neutrosophic set (NS), a part of neutrosophy theory, studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. The neutrosophic set is a general formal framework that has been recently proposed. However, the neutrosophic set needs to be specified from a technical point of view. Now, we apply the neutrosophic set into image domain and define some concepts and operators for image denoising.The imageGis transformed intoNSdomain, which is described using three membership sets:T,IandF. The entropy of the neutrosophic set is defined and employed to evaluate the indeterminancy. A new operation, γ-median-filtering operation, is proposed to decrease the set indeterminancy and remove noise. We have conducted experiments on a variety of noisy images using different types of noises with different levels. The experimental results demonstrate that the proposed approach can remove noise automatically and effectively. Especially, it can process not only noisy images with different levels of noise, but also images with different kinds of noise well without knowing the type of the noise, which is the most difficult task for image denoising.

Suggested Citation

  • Yanhui Guo & H. D. Cheng & Yingtao Zhang, 2009. "A New Neutrosophic Approach To Image Denoising," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 653-662.
    • Handle: RePEc:wsi:nmncxx:v:05:y:2009:i:03:n:s1793005709001490
    DOI: 10.1142/S1793005709001490
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    Cited by:

    1. Gholami, Maryam & Sheikhahmadi, Amir & Khamforoosh, Keyhan & Jalili, Mahdi, 2022. "Overlapping community detection in networks based on Neutrosophic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).

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