Weipei Jin, Jichang Guo, Qing Qi. Underwater Image Enhancement Based on Conditional Generative Adversarial Network[J]. Laser & Optoelectronics Progress, 2020, 57(14): 141002
- Laser & Optoelectronics Progress
- Vol. 57, Issue 14, 141002 (2020)
Fig. 1. Framework of StarGAN
Fig. 2. RRDB network structure. (a) RRDB module; (b) dense block structure
Fig. 3. Framework of the proposed method
Fig. 4. Network structure of generative model
Fig. 5. Network structure of discriminative model
Fig. 6. Four categories of label images. (a)Indoor image; (b) bluish underwater image; (c) greenish underwater image; (d) yellowish underwater image
Fig. 7. Sharpness results of synthesized underwater images. (a) Underwater images; (b) results of CLAHE algorithm; (c) results of RED algorithm; (d) results of CycleGAN algorithm; (e) results of UWGAN algorithm; (f) results of StarGAN algorithm; (g) results of proposed method; (h) original images
Fig. 8. Sharpness results of the bluish underwater images. (a) Underwater images; (b) results of CLAHE algorithm; (c) results of RED algorithm; (d) results of CycleGAN algorithm; (e) results of UWGAN algorithm; (f) results of StarGAN algorithm; (g) results of proposed method
Fig. 9. Sharpness results of the greenish underwater images. (a) Underwater images; (b) results of CLAHE algorithm; (c) results of RED algorithm; (d) results of CycleGAN algorithm; (e) results of UWGAN algorithm; (f) results of StarGAN algorithm; (g) results of proposed method
Fig. 10. Sharpness results of the yellowish underwater images. (a) Underwater images; (b) results of CLAHE algorithm; (c) results of RED algorithm; (d) results of CycleGAN algorithm; (e) results of UWGAN algorithm; (f) results of StarGAN algorithm; (g) results of proposed method
Fig. 11. Comparison of experimental results with different modules. (a) Underwater images; (b) results with residual block; (c) results of proposed method
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Table 1. Number of images used for training and testing
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Table 2. Comparison of UCIQE and information entropy using different methods in the synthesized image
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Table 3. Comparison of SSIM and MSE using different methods in the synthesized image
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Table 4. Comparison of UCIQE and information entropy using different methods in the real image
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Table 5. Comparison results of UCIQE and information entropy of different networks
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