Jialin Tang, Zebin Chen, Binghua Su, Keqin Li. Super-Resolution Restoration of Low Quality Face Images[J]. Laser & Optoelectronics Progress, 2018, 55(3): 031007
- Laser & Optoelectronics Progress
- Vol. 55, Issue 3, 031007 (2018)
Fig. 1. Face image decomposition
Fig. 2. Algorithm framework (a) fuzziness and down sampling; (b) face decomposition based on PCA; (c) MAP reasoning to get the best feature face; (d) constraint enhancement
Fig. 3. Test images
Fig. 4. Image processing results by different algorithms (×4). (a) Input images; (b) Bicubic method; (c) EigTran method; (d) ScSR method; (e) SRCNN method; (f) proposed algorithm; (g) original images
Fig. 5. Contrast experiment at n=819. (a) Input images; (b) Bicubic method; (c) proposed algorithm; (d) original image
Fig. 6. Effects of the number of training samples n on super-resolution restoration image PSNR
Fig. 7. Effects of the number of training samples n on super-resolution restoration image MSSIM
Fig. 8. Low-resolution face image processing without glasses. (a) Original high-resolution images; (b) low-resolution input images; (c) train set-1; (d) train set-2
Fig. 9. Low-resolution face image processing with glasses. (a) Original high-resolution images; (b) low-resolution input images; (c) train set-1; (d) train set-2
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Table 1. PSNR values of different algorithms
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