# An Advanced SAR Image Despeckling Method by Bernoulli-Sampling-Based Self-Supervised Deep Learning
## 3 Experimental Results and Analysis
### Despeckling Experiments on Synthetic Speckled Data
\begin{table}
\begin{tabular}{c l l c c c c c} \hline \hline
**Data** & **Index** & **PPB** & **SAR-BM3D** & **ID-CNN** & **SAR-DRN** & **SAR-RDCP** & **SSD-SAR-BS** \\ \hline \multirow{4}{*}{Airport} & PSNR & 21.6044 \(\pm\) 0.0797 & 22.4332 \(\pm\) 0.0726 & 22.5192 \(\pm\) 0.1544 & 23.6811 \(\pm\) 0.1186 & 23.7348 \(\pm\) 0.1291 & **24.3064 \(\pm\) 0.1637** \\  & SSIM & 0.4421 \(\pm\) 0.0033 & 0.5589 \(\pm\) 0.0025 & 0.5567 \(\pm\) 0.0012 & 0.6610 \(\pm\) 0.0008 & 0.6666 \(\pm\) 0.0028 & **0.7040 \(\pm\) 0.0029** \\  & ENL & 171.3710 \(\pm\) 12.1654 & 296.7359 \(\pm\) 22.8984 & 210.7900 \(\pm\) 10.1910 & 431.0681 \(\pm\) 33.3892 & 67.15572 \(\pm\) 32.9589 & **1033.1749 \(\pm\) 53.6550** \\ \hline \multirow{4}{*}{Beach} & PSNR & 19.1143 \(\pm\) 0.0904 & 20.1459 \(\pm\) 0.0842 & 19.9878 \(\pm\) 0.2748 & 20.4174 \(\pm\) 0.1308 & 20.2166 \(\pm\) 0.1325 & **20.4868 \(\pm\) 0.0903** \\  & SSIM & 0.3014 \(\pm\) 0.0048 & 0.4665 \(\pm\) 0.0031 & 0.4370 \(\pm\) 0.0057 & 0.5309 \(\pm\) 0.0034 & 0.5184 \(\pm\) 0.0017 & **0.5577 \(\pm\) 0.0010** \\  & ENL & 138.4539 \(\pm\) 9.2195 & 256.1158 \(\pm\) 39.5277 & 179.2292 \(\pm\) 8.0433 & 339.4192 \(\pm\) 16.4669 & 285.4422 \(\pm\) 17.5407 & **648.0094 \(\pm\) 61.1982** \\ \hline \multirow{4}{*}{Parking} & PSNR & 19.2132 \(\pm\) 0.0843 & 22.9632 \(\pm\) 0.0779 & 23.7254 \(\pm\) 0.1719 & 24.4793 \(\pm\) 0.1316 & 24.4762 \(\pm\) 0.1251 & **24.6219 \(\pm\) 0.1126** \\  & SSIM & 0.5047 \(\pm\) 0.0029 & 0.6599 \(\pm\) 0.0021 & 0.6566 \(\pm\) 0.0005 & 0.7107 \(\pm\) 0.0003 & 0.7121 \(\pm\) 0.0007 & **0.7306 \(\pm\) 0.0027** \\  & ENL & 139.1330 \(\pm\) 9.4936 & 198.7999 \(\pm\) 30.6818 & 102.3522 \(\pm\) 6.0899 & 223.5714 \(\pm\) 10.2016 & 220.4327 \(\pm\) 14.9143 & **596.4893 \(\pm\) 43.9951** \\ \hline \multirow{4}{*}{School} & PSNR & 19.5109 \(\pm\) 0.0890 & 20.9744 \(\pm\) 0.0836 & 21.1025 \(\pm\) 0.2659 & 21.6210 \(\pm\) 0.1105 & 21.5683 \(\pm\) 0.1467 & **21.9281 \(\pm\) 0.1305** \\  & SSIM & 0.3891 \(\pm\) 0.0037 & 0.5405 \(\pm\) 0.0026 & 0.5398 \(\pm\) 0.0066 & 0.5997 \(\pm\) 0.0016 & 0.6018 \(\pm\) 0.0028 & **0.6228 \(\pm\) 0.0015** \\  & ENL & 115.2169 \(\pm\) 8.2786 & 246.6993 \(\pm\) 38.0744 & 71.6737 \(\pm\) 5.0797 & 225.4230 \(\pm\) 12.7912 & 142.2418 \(\pm\) 9.1001 & **342.7139 \(\pm\) 17.3803** \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Quantitative evaluation results on synthetic speckled data. Figure 6: Despeckling results for the _Airport_ image. (**a**) Speckled. (**b**) PPB. (**c**) SAR-BM3D. (**d**) ID-CNN. (**e**) SAR-DRN. (**f**) SAR-RDCP. (**g**) Proposed SSD-SAR-BS. (**h**) Speckle-free reference. Figure 7: Despeckling results for the _Beach_ image. (**a**) Speckled. (**b**) PPB. (**c**) SAR-BM3D. (**d**) ID-CNN. (**e**) SAR-DRN. (**f**) SAR-RDCP. (**g**) Proposed SSD-SAR-BS. (**h**) Speckle-free reference. Figure 8: Despeckling results for the _Parking_ image. (**a**) Speckled. (**b**) PPB. (**c**) SAR-BM3D. (**d**) ID-CNN. (**e**) SAR-DRN. (**f**) SAR-RDCP. (**g**) Proposed SSD-SAR-BS. (**h**) Speckle-free reference. Figure 9: Despeckling results for the _School_ image. (**a**) Speckled. (**b**) PPB. (**c**) SAR-BM3D. (**d**) ID-CNN. (**e**) SAR-DRN. (**f**) SAR-RDCP. (**g**) Proposed SSD-SAR-BS. (**h**) Speckle-free reference.