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Sonar image super-resolution: stage-wise generative adversarial network with dual discriminators

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Abstract

In view of the inherent characteristics of sonar images such as low resolution and blurry target edges, this paper proposes a single image super-resolution reconstruction method based on generative adversarial networks, and verifies the reconstructed images by subjective and objective evaluation methods. Compared with the existing results, our proposed method has the following advantages: (i) this method uses two discriminators to constrain pixel and edge information separately, which helps to highlight target edges while improving image resolution; (ii) the generator of this method uses an upsampling module to upsample the image features in stages, which is beneficial to alleviate the mutual interference between low- and high-frequency information in the reconstruction process; (iii) on the premise of ensuring the reconstruction effect, we decrease the number of residual blocks in the generator.

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Data Availability

The datasets generated and analyzed during the current study are not publicly available due to restrictions from the data provider, as these data are also an integral part of ongoing research. However, they are available from the corresponding author on reasonable request.

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Funding

This work was supported by the Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences under Grant KY12400230016.

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Authors and Affiliations

  1. College of Mathematical Sciences, Harbin Engineering University, Harbin, 150001, Heilongjiang, People’s Republic of China

    Zeyu Dong, Chunbo Lian & Jihong Shen

  2. College of Shipbuilding Engineering, Harbin Engineering University, Harbin, 150001, Heilongjiang, People’s Republic of China

    Zhuo Wang

Authors
  1. Zeyu Dong
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  2. Zhuo Wang
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  3. Chunbo Lian
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  4. Jihong Shen
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Contributions

Zeyu Dong: Project administration, Visualization, Writing - original draft, Writing - review & editing, Investigation, Validation, Software, Methodology, Conceptualization. Zhuo Wang: Resources, Supervision, Writing - review & editing, Investigation, Formal analysis, Validation, Data curation. Chunbo Lian: Investigation, Writing - review & editing, Methodology. Jihong Shen: Funding acquisition, Supervision, Writing - review & editing, Resources, Formal analysis.

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Correspondence to Zhuo Wang or Jihong Shen.

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Dong, Z., Wang, Z., Lian, C. et al. Sonar image super-resolution: stage-wise generative adversarial network with dual discriminators. SIViP 19, 478 (2025). https://doi.org/10.1007/s11760-025-04014-w

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  • DOI: https://doi.org/10.1007/s11760-025-04014-w

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