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Image Denoising Using Generative Adversarial Network

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Intelligent Computing: Image Processing Based Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1157))

Abstract

Image denoising is one of the most important and fundamental research areas in the digital image-processing field. A noisy image can mislead image processing-based research. Therefore, image denoising is a critical area of research. In the recent advancement of computer vision, deep learning becomes most powerful tool. Deep learning is solving most of the problems, usually, which were earlier solved by various conventional techniques. The progress of deep learning encourages researchers to apply deep learning-based methods into image denoising also. In recent years, generative adversarial network (GAN) becomes a new avenue in computer vision research. The GANs are adversarial networks with generative capability, and the network has a very vast area of applications. In this chapter, we concentrate on a specific area of application of GAN—image denoising. At first, the traditional denoising techniques are highlighted. Then, we state the underlying architecture of GAN and its modifications. Then, we discuss the way GANs are applied in the area of image denoising. We survey all recent works of GANs in image denoising and categories those work according to the type of input images. In the end, we propose some research directions in this area. The compilation and discussions presented in this chapter regarding image denoising using GAN are new inclusion, and similar survey work is not available for the community.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Jadavpur University, Kolkata, India

    Ratnadeep Dey, Debotosh Bhattacharjee & Mita Nasipuri

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  1. Ratnadeep Dey
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  2. Debotosh Bhattacharjee
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  3. Mita Nasipuri
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Correspondence to Ratnadeep Dey .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, India

    J. K. Mandal

  2. Department of Electronics and Communication Engineering, University of Engineering and Management, Kolkata, West Bengal, India

    Soumen Banerjee

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Dey, R., Bhattacharjee, D., Nasipuri, M. (2020). Image Denoising Using Generative Adversarial Network. In: Mandal, J., Banerjee, S. (eds) Intelligent Computing: Image Processing Based Applications. Advances in Intelligent Systems and Computing, vol 1157. Springer, Singapore. https://doi.org/10.1007/978-981-15-4288-6_5

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