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Deep Convolutional Neural Network Based on Wavelet Transform for Super Image Resolution

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Hybrid Intelligent Systems (HIS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1375))

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Abstract

Recently, the biggest change in machine learning has demonstrated its ability to solve super resolution (SR) problems. Deep learning (DL) has been successfully applied to solve such problems. One of the most commonly used categories of SR is single image super resolution (SISR) which aims to reconstruct a high-resolution (HR) image from its low resolution (LR) image. This paper presents a deep neural network DNN based on convolutional Wavelet Transform for SISR. The DWT is applied to the LR image to divide it into various frequency components. Then, our deep convolutional neural network (DCNN) is fed with only the approximated image while dismissing their details in order to remove noise. To validate the effectiveness of the proposed method, extensive experiments are performed using Set5, Set14, and urban 100 datasets. The obtained results demonstrated the efficiency of the proposed approach.

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Author information

Authors and Affiliations

  1. National Engineering School of Gabes, Gabes, Tunisia

    Nesrine Chaibi, Asma Eladel & Mourad Zaied

  2. Research Team in Intelligent Machines (RTIM), Gabes, Tunisia

    Nesrine Chaibi & Mourad Zaied

Authors
  1. Nesrine Chaibi
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  2. Asma Eladel
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  3. Mourad Zaied
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Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Institute for Information Systems, University of Applied Sciences and Arts Northwestern Switzerland, Olten, Solothurn, Switzerland

    Thomas Hanne

  3. Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Mexico

    Oscar Castillo

  4. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, AL, USA

    Niketa Gandhi

  5. Universidade Federal da Bahia, Salvador, Bahia, Brazil

    Tatiane Nogueira Rios

  6. Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

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Chaibi, N., Eladel, A., Zaied, M. (2021). Deep Convolutional Neural Network Based on Wavelet Transform for Super Image Resolution. In: Abraham, A., Hanne, T., Castillo, O., Gandhi, N., Nogueira Rios, T., Hong, TP. (eds) Hybrid Intelligent Systems. HIS 2020. Advances in Intelligent Systems and Computing, vol 1375. Springer, Cham. https://doi.org/10.1007/978-3-030-73050-5_12

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