# Boosting of Denoising Effect with Fusion Strategy
## 4 Experiments
### Quantitative Comparison with Other State-of-the-Art Algorithms
The PSNR performance of the eight competing denoising methods is reported in Table 5. An overall impression, obtained from Table 5, is that the proposed method achieves the highest PSNR \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \(\sigma=10\) & \(\sigma=20\) & \(\sigma=30\) & \(\sigma=40\) & \(\sigma=50\) & \(\sigma=60\) \\ \hline NCSR & 0.637/0.983 & 0.494/0.959 & 0.413/0.934 & 0.376/0.910 & 0.343/0.886 & 0.313/0.860 \\ WNNM & 0.644/0.983 & 0.492/0.961 & 0.415/0.940 & 0.358/0.916 & 0.330/0.897 & 0.299/0.875 \\ PGPD & 0.622/0.982 & 0.475/0.959 & 0.403/0.937 & 0.353/0.914 & 0.320/0.891 & 0.280/0.871 \\ BM3D & 0.638/0.983 & 0.481/0.961 & 0.395/0.938 & 0.325/0.912 & 0.308/0.892 & 0.280/0.871 \\ DrCNN & 0.634/0.984 & 0.484/0.963 & 0.401/0.943 & 0.346/0.921 & 0.308/0.900 & 0.221/0.871 \\ TWSC & 0.578/0.984 & 0.416/0.936 & 0.333/0.941 & 0.280/0.918 & 0.242/0.894 & 0.212/0.871 \\ FFDNet & 0.636/0.984 & 0.492/0.964 & 0.417/0.945 & 0.366/0.924 & 0.333/0.904 & **0.309**/0.866 \\ proposed & **0.679**/**0.986** & **0.529**/**0.967** & **0.454**/**0.948** & **0.410**/**0.929** & **0.368**/**0.908** & 0.282/**0.885** \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Average VIF/ IW-SSIM values obtained for the competing methods evaluated on commonly used test images with noise level \(\sigma=10\), 20, 30, 40, 50 and 60. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **NCSR** & **WNNM** & **PGPD** & **BM3D** & **DnCNN** & **TWSC** & **FFDNet** & **Proposed** \\ \hline \(\sigma=10\) & 34.83 & 34.95 & 34.72 & 34.84 & 34.78 & 34.85 & 34.85 & **35.71** \\ \(\sigma=20\) & 31.38 & 31.59 & 31.33 & 31.42 & 31.64 & 31.56 & 31.70 & **31.92** \\ \(\sigma=30\) & 29.42 & 29.79 & 29.48 & 29.56 & 29.84 & 29.73 & 29.92 & **30.22** \\ \(\sigma=40\) & 28.06 & 28.46 & 28.25 & 28.09 & 28.58 & 28.42 & 28.67 & **28.96** \\ \(\sigma=50\) & 27.02 & 27.50 & 27.29 & 27.16 & 27.58 & 27.38 & 27.69 & **27.91** \\ \(\sigma=60\) & 26.07 & 26.67 & 26.41 & 26.38 & 26.25 & 26.51 & **26.92** & 26.90 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Average PSNRs (dB) of the competing methods evaluated on commonly used test images with noise level \(\sigma=10\), 20, 30, 40, 50 and 60. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \(\sigma=10\) & \(\sigma=20\) & \(\sigma=30\) & \(\sigma=40\) & \(\sigma=50\) & \(\sigma=60\) \\ \hline NCSR & 0.931/0.972 & 0.875/0.943 & 0.833/0.919 & 0.796/0.895 & 0.767/0.879 & 0.742/0.860 \\ WNNM & 0.931/0.972 & 0.877/0.944 & 0.839/0.923 & 0.802/0.902 & 0.778/0.885 & 0.752/0.871 \\ PGPD & 0.927/0.972 & 0.870/0.944 & 0.829/0.922 & 0.797/0.903 & 0.769/0.887 & 0.741/0.874 \\ BM3D & 0.931/0.972 & 0.876/0.946 & 0.834/0.924 & 0.795/0.903 & 0.767/0.888 & 0.743/0.874 \\ DrCNN & 0.931/0.971 & 0.883/0.946 & 0.844/0.926 & 0.811/0.908 & 0.782/0.892 & 0.717/0.879 \\ TWSC & 0.931/0.972 & 0.879/0.948 & 0.838/0.922 & 0.804/0.900 & 0.773/0.881 & 0.745/0.864 \\ FFDNet & 0.933/0.973 & **0.885**/0.948 & **0.848**/0.928 & **0.817**/0.910 & **0.790**/0.894 & **0.767**/0.881 \\ proposed & **0.936**/**0.976** & 0.883**/**0.951** & 0.847/**0.932** & 0.815/**0.913** & 0.788/**0.897** & 0.750/**0.888** \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Average SSIM/FSIM values obtained for the competing methods evaluated on commonly used test images with noise level \(\sigma=10\), 20, 30, 40, 50 and 60.  
in all cases. In the case of low noise levels (\(\sigma=10\)), the improvement is strikingly noticeable (e.g., an average improvement of 1.14 dB over the second-best method, FFDNet). Subsequently, even as the noise level increases to 50 and 60, the improvements exhibited by the proposed method over the PSNR of FFDNet are notable, with the average values of 0.13 dB and 0.03 dB, respectively. It is also observed that the proposed method outperforms the benchmark BM3D method by 0.65 dB\(\sim\)1.33 dB. Such a gain in the PSNR is remarkable because only a few methods can exceed the PSNR of the BM3D method by an average of more than 0.3 dB [48; 49].