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International Conference in Communications, Signal Processing, and Systems

CSPS 2018: Communications, Signal Processing, and Systems pp 52–58Cite as

Detection of White Gaussian Noise and Its Degree in Image Processing Using Generative Adversarial Nets

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 516))

Abstract

Since the theory of generative adversarial nets (GANs) put forward in 2014, various applications based on GANs have been developed. Most of the applications focused on generator network (G) of GANs to solve the daily challenges. However, rare of them had been aware of the great value of the discriminator network (D). In this paper, we propose a new method of detecting white Gaussian noise and its degree by the discriminator of generative adversarial nets. The results of our experiments show the feasibility of detecting white Gaussian noise (WGN) and evaluating its degree through generative adversarial nets.

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Author information

Authors and Affiliations

  1. College of Telecommunication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China

    Wentao Hua, Jian Xiong, Jie Yang & Guan Gui

Authors
  1. Wentao Hua
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  2. Jian Xiong
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  3. Jie Yang
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  4. Guan Gui
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Corresponding author

Correspondence to Jian Xiong .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA

    Qilian Liang

  2. School of Information and Communication Engineering, Dalian University of Technology, Dalian, China

    Xin Liu

  3. School of Information Science and Technology, Dalian Maritime University, Dalian, China

    Zhenyu Na

  4. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  5. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Jiasong Mu

  6. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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© 2020 Springer Nature Singapore Pte Ltd.

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Cite this paper

Hua, W., Xiong, J., Yang, J., Gui, G. (2020). Detection of White Gaussian Noise and Its Degree in Image Processing Using Generative Adversarial Nets. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-13-6504-1_7

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  • DOI: https://doi.org/10.1007/978-981-13-6504-1_7

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6503-4

  • Online ISBN: 978-981-13-6504-1

  • eBook Packages: EngineeringEngineering (R0)

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