Theory and Modern Applications
Table 2 Experimental results for different images and different blur kernels, \(\mathrm{BSNR}=40\)
From: Hybrid variational model based on alternating direction method for image restoration
Image | Blur kernels | Fast-TV [26] | FNDTV [27] | Proposed | |||
|---|---|---|---|---|---|---|---|
PSNR | SSIM | PSNR | SSIM | PSNR | SSIM | ||
cameraman | Gaussian(5, 5) | 28.6897 | 0.4841 | 29.2310 | 0.5061 | 29.6541 | 0.5208 |
Gaussian(7, 7) | 27.4559 | 0.4427 | 27.0594 | 0.4369 | 27.6590 | 0.4568 | |
Gaussian(9, 9) | 25.6219 | 0.4068 | 26.2835 | 0.4128 | 27.3563 | 0.4435 | |
couple | Gaussian(5, 5) | 32.0301 | 0.7718 | 32.8019 | 0.7942 | 33.5144 | 0.8202 |
Gaussian(7, 7) | 31.4577 | 0.7401 | 32.0764 | 0.7610 | 32.6735 | 0.7797 | |
Gaussian(9, 9) | 30.1657 | 0.6786 | 30.9071 | 0.7011 | 31.5687 | 0.7426 | |
lenna | average(7) | 32.0735 | 0.7049 | 32.5344 | 0.7279 | 33.3416 | 0.7526 |
average(9) | 31.0432 | 0.6500 | 31.8694 | 0.6853 | 32.7793 | 0.7312 | |
average(11) | 30.7127 | 0.6404 | 31.0552 | 0.6586 | 31.3851 | 0.6724 | |
goldhill | average(7) | 30.3156 | 0.6356 | 31.1560 | 0.6576 | 32.0284 | 0.6920 |
average(9) | 29.4280 | 0.6183 | 30.2251 | 0.6301 | 31.4493 | 0.6656 | |
average(11) | 28.3722 | 0.6082 | 29.5978 | 0.6202 | 30.6778 | 0.6464 | |
man | motion(20, 10) | 30.7569 | 0.6720 | 31.3522 | 0.7031 | 32.6930 | 0.7559 |
motion(11, 100) | 31.6579 | 0.7234 | 32.1598 | 0.7398 | 33.3935 | 0.8044 | |
baboon | motion(20, 10) | 30.3003 | 0.8837 | 30.6833 | 0.8993 | 31.5710 | 0.9128 |
motion(11, 100) | 31.4377 | 0.9082 | 31.9844 | 0.9245 | 32.5230 | 0.9323 | |