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Single Frame Image Super Resolution Using ANFIS Interpolation: An Initial Experiment-Based Approach

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Advances in Computational Intelligence Systems (UKCI 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1043))

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Abstract

Image super resolution is a classical problem in image processing. Different from most of the existing super resolution algorithms that work on sufficient training data, in this work, a new super resolution method is proposed to handle the situation where the training data is insufficient by the use of ANFIS (Adaptive Network-based Fuzzy Inference System) interpolation. ANFIS interpolation aims to interpolate an effective ANFIS given only sparse data in the problem area of interest, with the assistance of two well trained ANFISs in the neighbourhood areas. The interpolated ANFIS constructs mappings from low resolution images to high resolution ones, which provides an effective mechanism for further inference of high resolution images from given low resolution ones. Experimental results indicate that the proposed approach entails improved super resolution performance for situations where there is a shortage of training data.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Faculty of Business and Physical Sciences, Aberystwyth University, Aberystwyth, Ceredigion, Wales, UK

    Muhammad Ismail, Jing Yang, Changjing Shang & Qiang Shen

  2. Department of Computer Science, Sukkur IBA University, Sukkur, Sindh, Pakistan

    Muhammad Ismail

  3. School of Computer Science, Nortwestern Polytechnical University, Xi’an, 710072, China

    Jing Yang

Authors
  1. Muhammad Ismail
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  2. Jing Yang
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  3. Changjing Shang
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  4. Qiang Shen
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Corresponding author

Correspondence to Changjing Shang .

Editor information

Editors and Affiliations

  1. School of Computing, University of Portsmouth, Portsmouth, UK

    Zhaojie Ju

  2. Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, UK

    Longzhi Yang

  3. Bristol Robotics Laboratory, University of the West of England, Bristol, UK

    Chenguang Yang

  4. School of Computing, University of Portsmouth, Portsmouth, Hampshire, UK

    Alexander Gegov

  5. School of Computing, University of Portsmouth, Portsmouth, UK

    Dalin Zhou

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Ismail, M., Yang, J., Shang, C., Shen, Q. (2020). Single Frame Image Super Resolution Using ANFIS Interpolation: An Initial Experiment-Based Approach. In: Ju, Z., Yang, L., Yang, C., Gegov, A., Zhou, D. (eds) Advances in Computational Intelligence Systems. UKCI 2019. Advances in Intelligent Systems and Computing, vol 1043. Springer, Cham. https://doi.org/10.1007/978-3-030-29933-0_3

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