Underwater image enhancement algorithm based on improved U-Net
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School of Mechanical Engineering, Hebei University of Technology,Tianjin 300401,China

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TP391

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    Abstract:

    A new underwater image enhancement algorithm based on improved U-Net is proposed to address the problems of color distortion, fuzzy fogging, and low contrast in underwater degraded images. A new residual attention structure and edge detection module are designed and introduced into the U-Net network to construct the improved underwater image enhancement algorithm. The experimental results show that the algorithm proposed in this paper obtains good results in both correcting the underwater color bias and enhancing the contrast, with an average improvement of 14.2% in the IE value compared with the original image and an average improvement of 24% in the UCIQE value compared with the original image. The results of the ablation experiments show that the residual attention structure, edge detection module, and loss function proposed in this paper have positive effects on underwater image enhancement.

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  • Received:
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  • Online: April 30,2024
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