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Improved Feature Selection for Neighbor Embedding Super-Resolution Using Zernike Moments

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Proceedings of International Conference on Computer Vision and Image Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 460))

Abstract

This paper presents a new feature selection method for learning based single image super-resolution (SR). The performance of learning based SR strongly depends on the quality of the feature. Better features produce better co-occurrence relationship between low-resolution (LR) and high-resolution (HR) patches, which share the same local geometry in the manifold. In this paper, Zernike moment is used for feature selection. To generate a better feature vector, the luminance norm with three Zernike moments are considered, which preserves the global structure. Additionally, a global neighborhood selection method is used to overcome the problem of blurring effect due to over-fitting and under-fitting during K-nearest neighbor (KNN) search. Experimental analysis shows that the proposed scheme yields better recovery quality during HR reconstruction.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology, Rourkela, 769008, India

    Deepasikha Mishra, Banshidhar Majhi & Pankaj Kumar Sa

Authors
  1. Deepasikha Mishra
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  2. Banshidhar Majhi
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  3. Pankaj Kumar Sa
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Corresponding author

Correspondence to Deepasikha Mishra .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Balasubramanian Raman

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Sanjeev Kumar

  3. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Partha Pratim Roy

  4. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Debashis Sen

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Mishra, D., Majhi, B., Sa, P.K. (2017). Improved Feature Selection for Neighbor Embedding Super-Resolution Using Zernike Moments. In: Raman, B., Kumar, S., Roy, P., Sen, D. (eds) Proceedings of International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 460. Springer, Singapore. https://doi.org/10.1007/978-981-10-2107-7_2

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  • DOI: https://doi.org/10.1007/978-981-10-2107-7_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2106-0

  • Online ISBN: 978-981-10-2107-7

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