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A Survey of Image Super Resolution Based on CNN

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Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications (CloudComp 2019, SmartGift 2019)

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Abstract

With the advent of the information age in contemporary society, images are everywhere, no matter in military use or in daily life. Therefore, as a medium for people to obtain information, images have become more and more important. With the fast development of deep convolution neural networks (DCNNs), Single-Image Super-Resolution (SISR) becomes one of the techniques that have made great breakthroughs in recent years. In this paper, we give a brief survey on the task of SISR. In general, we introduce the SR problem, some recent SR methods, public benchmark datasets and evaluation metrics. Finally, we conclude by denoting some points that could be further improved in the future.

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Authors and Affiliations

  1. School of Computer and Software, Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, Nanjing, 210044, Jiangsu, China

    Qianxiong Xu & Yu Zheng

Authors
  1. Qianxiong Xu
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  2. Yu Zheng
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Corresponding author

Correspondence to Yu Zheng .

Editor information

Editors and Affiliations

  1. Macquarie University, Sydney, NSW, Australia

    Xuyun Zhang

  2. Macquarie University, Sydney, NSW, Australia

    Guanfeng Liu

  3. Pace University, New York, NY, USA

    Meikang Qiu

  4. James Cook University, Cairns, QLD, Australia

    Wei Xiang

  5. James Cook University, Smithfield, QLD, Australia

    Tao Huang

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Xu, Q., Zheng, Y. (2020). A Survey of Image Super Resolution Based on CNN. In: Zhang, X., Liu, G., Qiu, M., Xiang, W., Huang, T. (eds) Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications. CloudComp SmartGift 2019 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-030-48513-9_15

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  • DOI: https://doi.org/10.1007/978-3-030-48513-9_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-48512-2

  • Online ISBN: 978-3-030-48513-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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