Huan Chen, Qingjiang Chen. Scale-Perception Image Denoising Algorithm Based on Residual Learning[J]. Laser & Optoelectronics Progress, 2019, 56(9): 091005
- Laser & Optoelectronics Progress
- Vol. 56, Issue 9, 091005 (2019)
Fig. 1. Results of scale-perception and edge-protection filter acting on one-dimensional signals. (a)(b) Partial structures of one-dimensional signal I; (c)(d) result after one filtering process, R1; (e)(f) result after two filtering processes, R2; (g)(h) result after three filtering processes, R3
Fig. 2. Network structure of residual learning
Fig. 3. Framework of denoising algorithm
Fig. 4. Denoising results for image Butterfly under different algorithms. (a) Image Butterfly; (b) noise image; (c) DWT algorithm; (d) CNC algorithm; (e) NLM algorithm; (f) BM3D algorithm; (g) EPLL algorithm; (h) proposed algorithm
Fig. 5. Denoising results for image Lena under different algorithms. (a) Image Lena; (b) noise image; (c) DWT algorithm; (d) CNC algorithm; (e) NLM algorithm; (f) BM3D algorithm; (g) EPLL algorithm; (h) proposed algorithm
Fig. 6. Denoising results for image Man under different algorithms. (a) Image Man; (b) noise image; (c) DWT algorithm; (d) CNC algorithm; (e) NLM algorithm; (f) BM3D algorithm; (g) EPLL algorithm; (h) proposed algorithm
Fig. 7. Denoising results for image Pepper under different algorithms. (a) Image Pepper; (b) noise image; (c) DWT algorithm; (d) CNC algorithm; (e) NLM algorithm; (f) BM3D algorithm; (g) EPLL algorithm; (h) proposed algorithm
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Table 1. Comparison of PSNR values of test images under different algorithmsdB
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Table 2. Comparison of SSIM values of test images under different algorithmsdB
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