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Laplacian Pyramid-like Autoencoder

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Intelligent Computing (SAI 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 507))

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Abstract

In this paper, we develop the Laplacian pyramid-like autoencoder (LPAE) by adding the Laplacian pyramid (LP) concept widely used to analyze images in Signal Processing. LPAE decomposes an image into the approximation image and the detail image in the encoder part and then tries to reconstruct the original image in the decoder part using the two components. We use LPAE for experiments on classifications and super-resolution areas. Using the detail image and the smaller-sized approximation image as inputs of a classification network, our LPAE makes the model lighter. Moreover, we show that the performance of the connected classification networks has remained substantially high. In a super-resolution area, we show that the decoder part gets a high-quality reconstruction image by setting to resemble the structure of LP. Consequently, LPAE improves the original results by combining the decoder part of the autoencoder and the super-resolution network.

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Acknowledgments

T. Hur—This work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government(MSIT) (No.2021-0-00023, Developing a lightweight Korean text detection and recognition technology for complex disaster situations).

Y. Hur—This work was supported in part by National Research Foundation of Korea (NRF) [Grant Numbers 2015R1A5A1009350 and 2021R1A2C1007598], and by the ‘Ministry of Science and ICT’ and NIPA via “HPC Support” Project.

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Authors and Affiliations

  1. School of Mathematics and Computing (Mathematics), Yonsei University, Seoul, South Korea

    Sangjun Han

  2. JENTI Inc., Seoul, South Korea

    Taeil Hur

  3. Department of Mathematics, Yonsei University, Seoul, South Korea

    Youngmi Hur

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  1. Sangjun Han
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  2. Taeil Hur
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Correspondence to Youngmi Hur .

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Editors and Affiliations

  1. Saga University, Saga, Japan

    Kohei Arai

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Han, S., Hur, T., Hur, Y. (2022). Laplacian Pyramid-like Autoencoder. In: Arai, K. (eds) Intelligent Computing. SAI 2022. Lecture Notes in Networks and Systems, vol 507. Springer, Cham. https://doi.org/10.1007/978-3-031-10464-0_5

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