## 4 Experimental Results and Analysis
### Quantitative Results
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Noise** & \multicolumn{2}{c}{**Image R1**} & **Image R2** & **Image R3** & **Image R4** & **Image R5** & **Image R6** \\ \cline{3-8}
**Density** & \multicolumn{2}{c}{**SSIM Values**} & & & & & \\ \hline
5\% & 0.945185 & 0.943385 & 0.942513 & 0.937519 & 0.936408 & 0.934789 \\ \hline
10\% & 0.926260 & 0.925201 & 0.924620 & 0.920162 & 0.919456 & 0.917345 \\ \hline
15\% & 0.910734 & 0.910573 & 0.910914 & 0.905187 & 0.904893 & 0.904291 \\ \hline
20\% & 0.901130 & 0.900996 & 0.898911 & 0.893868 & 0.893466 & 0.892968 \\ \hline
25\% & 0.883405 & 0.883405 & 0.880901 & 0.876379 & 0.875789 & 0.874897 \\ \hline
30\% & 0.865680 & 0.865809 & 0.863623 & 0.859061 & 0.858735 & 0.857798 \\ \hline
35\% & 0.847955 & 0.847882 & 0.845612 & 0.840414 & 0.846746 & 0.846345 \\ \hline
40\% & 0.830230 & 0.830382 & 0.828658 & 0.825006 & 0.825534 & 0.824784 \\ \hline
45\% & 0.812505 & 0.812528 & 0.811728 & 0.810150 & 0.811231 & 0.810543 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: SSIM values for images R1, R2, R3, R4, R5, and R6 at various noise intensities. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Denoising Scheme** & \multicolumn{5}{c}{**Gaussian Blur Noise at Different Intensities (\%)**} \\ \cline{2-7}  & **35\%** & **40\%** & **45\%** & **50\%** & **55\%** & **60\%** \\ \hline Non-Local Means [23] & 6.8752 & 6.9932 & 5.0735 & 4.4100 & 3.8214 & 3.3328 \\ \hline Gaussian [24] & 9.6175 & 7.6793 & 6.7695 & 6.2262 & 5.6484 & 5.1261 \\ \hline Median [25] & 9.6986 & 8.1305 & 7.2202 & 6.5345 & 5.9930 & 5.4779 \\ \hline DWT [27] & 6.5986 & 6.5467 & 5.0032 & 4.1264 & 3.4574 & 3.0042 \\ \hline Mean [28] & 9.9898 & 8.1453 & 7.2461 & 6.5730 & 5.9483 & 5.4735 \\ \hline Wiener [42] & 7.8863 & 7.0043 & 6.1846 & 5.4212 & 4.9325 & 4.4439 \\ \hline DnCNN [56] & 5.6845 & 5.8697 & 4.7589 & 3.6895 & 2.8964 & 2.6874 \\ \hline Proposed Approach & 4.6978 & 4.5535 & 2.8975 & 2.4967 & 2.1895 & 1.4984 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._ \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**IMAGE** & \multicolumn{1}{c}{**Median**} & \multirow{2}{*}{**Mean [28]**} & \multirow{2}{*}{**Wiener**} & \multirow{2}{*}{**Gaussian**} & \multirow{2}{*}{**NLM**} & \multirow{2}{*}{**DWT [27]**} & **DnCNN** & **Proposed** \\  & [25] & & [42] & & [24] & [23] & & [56] & **Approach** \\ \hline Image R1 & 29.7189 & 29.7290 & 24.5629 & 24.5736 & 39.3783 & 29.3783 & 29.2486 & 26.4634 \\ \hline Image R2 & 69.3731 & 69.9344 & 227.4001 & 218.8388 & 97.0323 & 85.0321 & 80.9547 & 70.9867 \\ \hline Image R3 & 236.6997 & 487.1047 & 575.0933 & 815.4983 & 137.1280 & 127.1280 & 111.8759 & 101.3453 \\ \hline Image R4 & 276.3539 & 526.7589 & 614.7475 & 855.1525 & 166.7822 & 156.7822 & 158.0136 & 135.6523 \\ \hline Image R5 & 325.3523 & 630.4532 & 640.8953 & 916.2461 & 186.0234 & 176.0234 & 165.8954 & 156.8953 \\ \hline Image R6 & 386.2341 & 689.2313 & 705.7646 & 947.9875 & 255.2488 & 245.3478 & 230.8694 & 206.9078 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of MSE values of different filtering schemes, including wiener, mean, median, DWT, Gaussian, NLM filter, and DnCNN with the proposed approach for selected CT images R1, R2, R3, R4, R5, and R6. Figure 4: (**a**) PSNR for different denoising schemes at various AGBN intensities for images R1, R2, R3, R4, R5, and R6 (5–30% noise intensity). (**b**) PSNR for different denoising schemes at various AGBN intensities for images R1, R2, R3, R4, R5, and R6 (35–60% noise intensity).