利用生成对抗网络实现水下图像增强
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李钰, 杨道勇, 刘玲亚, 王易因
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Underwater Image Enhancement Based on Generative Adversarial Networks
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LI Yu, YANG Daoyong, LIU Lingya, WANG Yiyin
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表2 各增强算法在合成数据集上的评价指标对比
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Tab.2 Metrics comparison of various enhancement algorithms on synthetic datasets
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算法 | PSNR | SSIM | UIQM | CCF | 信息熵 | 原图 | 17.180 | 0.628 | 2.589 | 24.285 | 7.135 | 文献[23] | 14.782 | 0.567 | 2.892 | 23.308 | 7.526 | 文献[24] | 18.063 | 0.686 | 2.409 | 26.919 | 7.547 | 文献[25] | 16.507 | 0.657 | 2.699 | 25.787 | 7.744 | 文献[26] | 18.612 | 0.714 | 3.216 | 26.866 | 7.519 | 文献[13] | 18.776 | 0.698 | 3.219 | 27.710 | 7.262 | 文献[27] | 16.153 | 0.588 | 2.995 | 16.997 | 6.749 | 本文算法 | 26.094 | 0.835 | 3.378 | 31.139 | 7.786 |
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