## 3 Proposed Technique
### Watermark Extraction Process
Furthermore, upon conducting a comparative analysis of the outcomes with other extant methodologies, namely [28; 30; 31; 32], at intensities of 0.05, 0.025, and 0.10 (as presented in Table 5), it was noted that the findings of [31; 32] bear similarity to the suggested approach at an intensity of 0.050. At the intensity of 0.025 and 0.010, the performance of our approach is much better than other similar schemes. Thus, it can be inferred that the proposed methodology exhibited superior performance compared to various analogous methodologies. #### 4.1.3 Noise Addition Attack

The susceptibility of the proposed scheme to noise interference on the watermarked image has been assessed. Different levels of noise, ranging from 0.001 to 0.020, were applied to the watermarked image. Subsequently, the watermark was extracted from the distorted image, as illustrated in Figure 9. As depicted in Figure 9, the extraction of the watermark from a distorted watermarked image is feasible even in the presence of a noise attack. The aforementioned outcome exhibits the durability of the watermarking methodology, \begin{table}
\begin{tabular}{c c c} \hline \hline \(\mathbf{\alpha}\) & **NC** & **SSIM** \\ \hline
0.0500 & 0.7211 & 0.7332 \\
0.0250 & 0.7713 & 0.7881 \\
0.0100 & 0.8213 & 0.8551 \\
0.0050 & 0.8479 & 0.8643 \\
0.0020 & 0.9331 & 0.8997 \\
0.0010 & 1.0000 & 0.9887 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Filtering Attack: NC and SSIM of Extracted Watermark. Figure 8: Extracted Watermark after Filtering Attack. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \(\mathbf{\alpha}\) & **Proposed Work** & [28] & [31] & [30] & [32] \\ \hline
0.0500 & 0.7211 & 0.6331 & 0.7089 & 0.6811 & 0.7298 \\
0.0250 & 0.7713 & 0.6597 & 0.7221 & 0.7212 & 0.7399 \\
0.0100 & 0.8213 & 0.7712 & 0.7689 & 0.7551 & 0.7611 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison of NC value on Filter Attack. indicating potential for future applications. Table 6 displays the outcomes of watermark extraction from an image that has been watermarked and exposed to different levels of noise. The NC values corresponding to the intensity levels of 0.020, 0.010, 0.005, and 0.001 are 0.9715, 0.9791, 1.0000, and 1.0000, respectively. The SSIM values for intensity levels of 0.020, 0.010, 0.005, and 0.001 are reported as 0.8971, 0.9001, 0.9881, and 0.9891, respectively. The attained NC and SSIM values in our experiment serve as a promising foundation for subsequent analysis. The findings indicate that the envisaged system exhibited satisfactory performance even in the presence of a noise attack. In addition, a comparative analysis was performed to evaluate the results of the proposed methodology in relation to other established approaches, specifically [28; 30; 31; 32], with respect to varying noise intensity levels of 0.001, 0.005, 0.010, and 0.020 (as presented in Table 7). The findings indicate that the outcomes of [28; 30] bear a resemblance to the proposed scheme at intensity levels of 0.001 and 0.020. At an intensity level of 0.010, it is apparent that [30; 31; 32] exhibit superior performance. However, the performance of intensity level 0.005 surpasses that of [28; 30; 31; 32]. Therefore, it can be deduced that the suggested approach demonstrated better results when compared to several similar approaches. #### 4.1.4 Histogram Equalization Attack

Table 8 shows the histogram equalization attack on the watermarked image. Based on the preceding discourse, the benefits of the suggested plan are outlined as follows:

1. The proposed scheme's PSNR is higher than that of other existing systems, demonstrating that the watermarked image quality is suitable for diagnosis. 2. The robustness of the proposed scheme is found better with similar existing schemes in various cases. However, in some attacks, its performance is quite similar.