## 4 Experiments
### Experimental Results and Analysis
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{5}{c}{**Noise Level**} \\ \cline{2-7}  & \(\sigma\) = 10 & \(\sigma\) = 20 & \(\sigma\) = 30 & \(\sigma\) = 40 & \(\sigma\) = 50 & \(\sigma\) = 60 \\ \hline BM3D & 34.82 & 31.44 & 29.59 & 28.13 & 27.54 & 26.37 \\ FFDNet & 34.86 & 31.72 & 29.95 & 28.70 & 27.73 & 26.92 \\ NCSR & 34.81 & 31.38 & 29.43 & 28.06 & 27.02 & 26.08 \\ DnCNN & 34.94 & 31.69 & 29.83 & 28.52 & 27.56 & 26.65 \\ WNNM & 35.01 & 31.61 & 29.80 & 28.48 & 27.51 & 26.68 \\ RED-Net & 34.25 & 31.13 & 29.44 & 28.23 & 27.26 & 26.46 \\ TWSC & 34.85 & 31.56 & 29.73 & 28.42 & 27.38 & 26.51 \\ CsNet & 34.62 & 31.40 & 29.75 & 28.55 & 27.61 & 26.79 \\ DIP & 33.44 & 30.16 & 28.36 & 26.99 & 25.93 & 24.98 \\ Proposed & **35.34** & **32.95** & **31.08** & **29.71** & **28.51** & **27.71** \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Average PSNR results of different methods on 10 commonly used images with various noise levels. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{5}{c}{**Noise Level**} \\ \cline{2-7}  & \(\sigma\) = 10 & \(\sigma\) = 20 & \(\sigma\) = 30 & \(\sigma\) = 40 & \(\sigma\) = 50 & \(\sigma\) = 60 \\ \hline BM3D & 0.9306 & 0.8764 & 0.8348 & 0.7968 & 0.7701 & 0.7436 \\ FFDNet & 0.9330 & 0.8855 & 0.8487 & 0.8177 & 0.7908 & 0.7668 \\ NCSR & 0.9307 & 0.8745 & 0.8289 & 0.7960 & 0.7668 & 0.8603 \\ DnCNN & 0.9327 & 0.8829 & 0.8432 & 0.8093 & 0.7823 & 0.7523 \\ WNNM & 0.9311 & 0.8773 & 0.8356 & 0.8024 & 0.7779 & 0.8700 \\ RED-Net & 0.9197 & 0.8694 & 0.8315 & 0.7986 & 0.7698 & 0.7443 \\ TWSC & 0.9313 & 0.8787 & 0.8380 & 0.8035 & 0.7727 & 0.7446 \\ CsNet & 0.9251 & 0.8756 & 0.8405 & 0.8100 & 0.7831 & 0.7581 \\ DIP & 0.9490 & 0.9490 & 0.8689 & 0.8333 & 0.8056 & 0.7805 \\ Proposed & **0.9675** & **0.9502** & **0.9290** & **0.9077** & **0.8887** & **0.8706** \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Average SSIM results of different methods on 10 commonly used images with various noise levels. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{5}{c}{**Noise Level**} \\ \cline{2-7}  & \(\sigma\) = 10 & \(\sigma\) = 20 & \(\sigma\) = 30 & \(\sigma\) = 40 & \(\sigma\) = 50 & \(\sigma\) = 60 \\ \hline BM3D & 0.9717 & 0.9452 & 0.9239 & 0.9038 & 0.8883 & 0.8737 \\ FFDNet & 0.9723 & 0.9476 & 0.9278 & 0.9103 & 0.8947 & 0.8806 \\ NCSR & 0.9719 & 0.9435 & 0.9196 & 0.8956 & 0.8789 & 0.7414 \\ DnCNN & 0.9720 & 0.9472 & 0.9266 & 0.9078 & 0.8923 & 0.8771 \\ WNNM & 0.9713 & 0.9444 & 0.9233 & 0.9031 & 0.8863 & 0.7508 \\ RED-Net & 0.9698 & 0.9454 & 0.9251 & 0.9068 & 0.8908 & 0.8770 \\ TWSC & 0.9719 & 0.9448 & 0.9215 & 0.9003 & 0.8815 & 0.8641 \\ CsNet & 0.9718 & 0.9475 & 0.9280 & 0.9099 & 0.8938 & 0.8797 \\ DIP & 0.9663 & 0.9393 & 0.9170 & 0.8977 & 0.8817 & 0.8659 \\ Proposed & **0.9762** & **0.9615** & **0.9457** & **0.9154** & **0.9154** & **0.9030** \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Average FSIM results of different methods on 10 commonly used images with various noise levels. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{5}{c}{**Noise Level**} \\ \cline{2-7}  & \(\sigma\) = **10** & \(\sigma\) = **20** & \(\sigma\) = **30** & \(\sigma\) = **40** & \(\sigma\) = **50** & \(\sigma\) = **60** \\ \hline BM3D & 0.9219 & 0.8404 & 0.7836 & 0.7390 & 0.7041 & 0.6758 \\ FFDNet & 0.9289 & 0.8606 & 0.8101 & 0.7690 & 0.7355 & 0.7076 \\ NCSR & 0.9243 & 0.8420 & 0.7860 & 0.7373 & 0.7032 & 0.6732 \\ DrCNN & 0.9295 & 0.8592 & 0.8064 & 0.7632 & 0.7298 & 0.6986 \\ WNNM & 0.9248 & 0.8449 & 0.7904 & 0.7460 & 0.7140 & 0.6844 \\ RED-Net & 0.9229 & 0.8423 & 0.7826 & 0.7352 & 0.6974 & 0.6673 \\ TWSC & 0.9267 & 0.8451 & 0.7775 & 0.7243 & 0.6822 & 0.6483 \\ CsNet & 0.9260 & 0.8474 & 0.7895 & 0.7440 & 0.7059 & 0.6731 \\ DIP & 0.9488 & 0.9002 & 0.8564 & 0.8206 & 0.7894 & 0.7614 \\ Proposed & **0.9717** & **0.9402** & **0.9101** & **0.8797** & **0.8528** & **0.8303** \\ \hline \hline \end{tabular}
\end{table}