Research Article
A Nonmonotone Gradient Algorithm for Total Variation Image Denoising Problems
Table 1
Numerical comparison for images (a)–(d) in Figure
1.
| | Barbara | Boats | Satellite | Pepper | Average | | PSNR | Error | PSNR | Error | PSNR | Error | PSNR | Error | PSNR | Error |
| PG_Chambolle | 28.8919 | 0.0735 | 29.1882 | 0.0654 | 29.5731 | 0.1077 | 29.4148 | 0.0662 | 29.2670 | 0.0782 | SPG_Birgin | 29.7996 | 0.0662 | 30.4961 | 0.0562 | 32.4344 | 0.0775 | 30.8096 | 0.0564 | 30.8849 | 0.0641 | FPG_Beck | 28.9254 | 0.0732 | 29.2779 | 0.0647 | 31.2876 | 0.0884 | 29.4227 | 0.0661 | 29.7284 | 0.0731 | ASPG | 30.2991 | 0.0625 | 31.3927 | 0.0507 | 32.6485 | 0.0756 | 32.0317 | 0.0490 | 31.5930 | 0.0594 |
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