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Research on Image Super-Resolution Reconstruction of Optical Image

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Book cover Communications, Signal Processing, and Systems (CSPS 2018)

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

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Abstract

Currently, the image super-resolution reconstruction method based on sparse representation has limited ability to process the details of the edge. Therefore, based on the dictionary learning, the local variance feature edge gradient estimation image fast super-resolution reconstruction is improved and optimized based on dictionary training. The dictionary training process includes cluster analysis of high-resolution images, local variance extraction, and sparse filtering. The reconstruction process includes local variance detection of the low-resolution image and threshold judgment, and then the image is reconstructed according to the gradient value.

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References

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Acknowledgements

This work is supported in part by the National Natural Science Foundation China (61601174), in part by the Postdoctoral Research Foundation of Heilongjiang Province (LBH-Q17150), in part by the Science and Technology Innovative Research Team in Higher Educational Institutions of Heilongjiang Province (No. 2012TD007),in part by the Fundamental Research Funds for the Heilongjiang Provincial Universities (KJCXZD201703), and in part by the Science Foundation of Heilongjiang Province of China (F2018026).

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Authors and Affiliations

  1. Heilongjiang University, Harbin, China

    Aiping Jiang, Xinwei Li & Han Gao

Authors
  1. Aiping Jiang
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  2. Xinwei Li
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  3. Han Gao
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Corresponding author

Correspondence to Aiping Jiang .

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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© 2020 Springer Nature Singapore Pte Ltd.

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Cite this paper

Jiang, A., Li, X., Gao, H. (2020). Research on Image Super-Resolution Reconstruction of Optical Image. 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_30

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  • DOI: https://doi.org/10.1007/978-981-13-6504-1_30

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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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