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A cupping spots image enhancement algorithm based on LAA-CycleGAN

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Abstract

During the automatic cupping process, a LAA-CycleGAN-based image enhancement algorithm is proposed to address the issues of reduced image clarity and loss of detail features caused by fog adhering to the surface of the can body. Firstly, the generator contains a self-attention module to capture global features of the images; secondly, the discriminator introduces an auto-encoder to generate more stable images; finally, a perceptual loss term is added to optimize the network for better perception. Experiments were conducted on the collected cupping spots dataset, and the results showed that compared with DCP, DehazeNet, AOD-Net, and CycleGAN algorithms, SSIM values increased by 48.78%, 61.02%, 53.45%, and 85.42%, while PSNR values increased by 5.02%, 5.09%, 4.78%, and 4.27%. The algorithm in this article reconstructs the cupping spots image with higher clarity, which can effectively enhance the quality of the cupping spots image and preserve details.

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These data that support the findings of this study are available from the corresponding author upon reasonable request.

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Funding

This work was supported by the National Natural Science Foundation of China (No. 61961011) and the National Natural Science Foundation of China (No. 61650106).

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Authors and Affiliations

  1. Key Laboratory of Advanced Manufacturing and Automation Technology (Guilin University of Technology), Education Department of Guangxi Zhuang Autonomous Region, Guilin, 541006, China

    Jianhua Qin

  2. College of Mechanical and Control Engineering Guilin University of Technology, Guilin, 541004, China

    Jianhua Qin, Mengyan Zhu & Yingbin Liu

  3. Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, China

    Guifen Zeng & Baolin Xu

Authors
  1. Jianhua Qin
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  2. Mengyan Zhu
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  3. Yingbin Liu
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  4. Guifen Zeng
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  5. Baolin Xu
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All authors reviewed the manuscript

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Correspondence to Jianhua Qin.

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The study protocol was approved by the ethics review board of Guilin University of Technology. All of the procedures were performed in accordance with the Declaration of Helsinki and relevant policies in China.

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Qin, J., Zhu, M., Liu, Y. et al. A cupping spots image enhancement algorithm based on LAA-CycleGAN. SIViP 18, 3155–3162 (2024). https://doi.org/10.1007/s11760-023-02978-1

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  • DOI: https://doi.org/10.1007/s11760-023-02978-1

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