Optical image super-resolution in dark underwater background via SwinIR

Qi Li; Jun Wang; Hongna Zhu; Kequan Shi; Hao Sui; Yongsheng Zhao; Qian Ni; Yanqun Wu

doi:10.1117/12.3004152

24 November 2023 Optical image super-resolution in dark underwater background via SwinIR

Qi Li, Jun Wang, Hongna Zhu, Kequan Shi, Hao Sui, Yongsheng Zhao, Qian Ni, Yanqun Wu

Proceedings Volume 12935, Fourteenth International Conference on Information Optics and Photonics (CIOP 2023); 129350R (2023) https://doi.org/10.1117/12.3004152
Event: Fourteenth International Conference on Information Optics and Photonics (CIOP 2023), 2023, Xi’an, China

Abstract

The optical images quality in dark underwater background is usually degraded, influencing the results of accurate identification, terrain mapping and seabed exploration. Thus, the super-resolution methods for dark underwater optical images attract extensive research interest. In this work, the SwinIR model is provided for dark underwater optical images super-resolution. Here, the EUVP DARK dataset with dark underwater background is employed, which clusters 5500 paired images. The SwinIR networks has high speed of process with large-size image capability and plentiful image detail. Compared with the traditional SRGAN method, the super-resolution reconstruction speed increases about 18.3%, and the peak pignal-to-noise ratio (PSNR) and structural similarity (SSIM) of SwinIR test results on the EUVP DARK dataset increase by 14.4% and 15.8% respectively, the results illustrate that our method improving the accuracy and quality of reconstruction. In conclusion, the hierarchical structure of SwinIR and self-attention mechanism adaptive attention weights in generated to the image, enabling precise adjustment and control of detail and texture. This method provides an efficient approach to dark underwater image quality enhancement.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qi Li, Jun Wang, Hongna Zhu, Kequan Shi, Hao Sui, Yongsheng Zhao, Qian Ni, and Yanqun Wu "Optical image super-resolution in dark underwater background via SwinIR", Proc. SPIE 12935, Fourteenth International Conference on Information Optics and Photonics (CIOP 2023), 129350R (24 November 2023); https://doi.org/10.1117/12.3004152

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KEYWORDS

Super resolution

Transformers

Feature extraction

Image processing

Image restoration

Image quality

Ocean optics

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