Fig. 1. Network structure of DRSA-Net

Fig. 2. Flow chart of retinal OCT image unsupervised training experiment

Fig. 3. Noise reduction in retinal OCT images. (a) Original noisy image; (b) denoised images of BM3D; (c) denoised image of DnCNN-N2N; (d) 5-frame average ground truth images; (e) denoised image of U-Net-N2N; (f) denoised image of Ours-N2N

Fig. 4. Noise reduction results of supervised learning and unsupervised learning retinal OCT images. (a) Original noisy image; (b) denoised image of DnCNN-N2C; (c) denoised image of U-Net-N2C; (d) denoised image of Ours-N2C; (e) 5-frame average ground truth image; (f) denoised image of DnCNN-N2N; (g) denoised image of U-Net-N2N; (h) denoised image of Ours-N2N

Fig. 5. Unsupervised learning generalization ability test. (a) Original noisy image; (b) denoised images of BM3D; (c) denoised image of DnCNN-N2N; (d) 40-frame average ground truth images; (e) denoised image of U-Net-N2N; (f) denoised image of Ours-N2N

Fig. 6. Comparison of generalization ability between supervised and unsupervised learning. (a) Denoised image of DnCNN-N2C; (b) denoised image of U-Net-N2C; (c) denoised image of Ours-N2C; (d) denoised image of DnCNN-N2N; (e) denoised image of U-Net-N2N; (f) denoised image of Ours-N2N

Table 1. Results of supervised learning and unsupervised learning denoising numerical evaluation

Table 2. Results of supervised learning and unsupervised learning denoising numerical evaluation

Table 3. Ablation experimental results of different modules of network