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Single-Image Super-Resolution: A Survey

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Communications, Signal Processing, and Systems (CSPS 2018)

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

Abstract

Single-image super-resolution has been broadly applied in many fields such as military term, medical imaging, etc. In this paper, we mainly focus on the researches of recent years and classify them into non-deep learning SR algorithms and deep learning SR algorithms. For each classification, the basic concepts and algorithm processes are introduced. Furthermore, the paper discusses the advantages and disadvantages of different algorithms, which will offer potential research direction for the future development of SR.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 31700742), the Young Elite Scientist Sponsorship Program by CAST (2017QNRC001) and the Fundamental Research Funds for the Central Universities (No. 3132018306, 3132018180, 3132018172).

Author information

Authors and Affiliations

  1. College of Information Science and Technology, Collaborative Innovation Research Institute of Autonomous Ship, Dalian Maritime University, Dalian, China

    Tingting Yao, Yu Luo, Yantong Chen & Dongqiao Yang

  2. Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian, China

    Lei Zhao

Authors
  1. Tingting Yao
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  2. Yu Luo
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  3. Yantong Chen
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  4. Dongqiao Yang
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  5. Lei Zhao
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Corresponding author

Correspondence to Lei Zhao .

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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Yao, T., Luo, Y., Chen, Y., Yang, D., Zhao, L. (2020). Single-Image Super-Resolution: A Survey. 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_16

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  • DOI: https://doi.org/10.1007/978-981-13-6504-1_16

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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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