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Image Super Resolution Reconstruction Algorithm Based on Multiple Prior Constraints

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Communications, Signal Processing, and Systems (CSPS 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1032))

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Abstract

High spatial resolution is necessary for several applications such as visual inspection. However, the conflict between resolution and image distance limits the applications of image devices. In this paper, a super-resolution framework with multiple priors is proposed. Firstly, the directional generalized total variational and the non-local self-similar constraint are incorporated to enhance image texture details and smooth edge effects. Especially, an adaptive Gaussian kernel is used to better descript the non-local prior. Secondly, the proposed multi-constraint problem is solved by the alternate direction multiplier method. Generally, a large number of qualitative and quantitative results demonstrated the effectiveness and superiority of our method over traditional methods.

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Author information

Authors and Affiliations

  1. College of Marine Electrical Engineering, Dalian Maritime University, Dalian, 116026, China

    Ting Liu & Kun Wang

Authors
  1. Ting Liu
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  2. Kun Wang
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Corresponding author

Correspondence to Ting Liu .

Editor information

Editors and Affiliations

  1. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  2. 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

    Baoju Zhang

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Liu, T., Wang, K. (2024). Image Super Resolution Reconstruction Algorithm Based on Multiple Prior Constraints. In: Wang, W., Liu, X., Na, Z., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2023. Lecture Notes in Electrical Engineering, vol 1032. Springer, Singapore. https://doi.org/10.1007/978-981-99-7505-1_38

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  • DOI: https://doi.org/10.1007/978-981-99-7505-1_38

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-7539-6

  • Online ISBN: 978-981-99-7505-1

  • eBook Packages: EngineeringEngineering (R0)

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