## 6 Experimental Results and Discussion
### Comparison with State-of-the-Art Schemes  
The proposed SR-HTR method was compared in terms of performance with other state-of-the-art methods. As previously mentioned, the design of SR-HTR aims to achieve high performance when there is a high rate of modification in a watermarked image. This is accomplished by the insertion of redundancy in the authentication and reconstruction bits. Therefore, the comparison is performed in terms of objective quality in the following areas: watermarked image visualization, change detection rates and reconstruction image visualization. The first evaluation consists of the comparison between the watermarked image and the original one. Table 6 shows the average values of PSNR, SSIM and PSNR-HVS-M for the set of test images employed. The novel SR-HTR method and [PERSON] [36] present the best quality results in PSNR and SSIM. This is due to the bit adjustment stage implemented in 2-LSB for both methods. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **PSNR (dB)** & **SSIM** & **PSNR-HVS (dB)** \\ \hline SR-HTR & 44.33 & 0.9843 & 49.69 \\ [PERSON] [36] & 44.32 & 0.9845 & 49.36 \\ [PERSON] [23] & 44.08 & 0.9832 & 50.09 \\ [PERSON] [2] & 37.85 & 0.9364 & 42.04 \\ [PERSON] [24] & 44.08 & 0.9832 & 50.07 \\ [PERSON] [10] & 37.85 & 0.9363 & 42.05 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Quality comparison using PSNR, SSIM and PSNR-HVS-M between watermarked images and original ones. Figure 11: Reconstructed images from multiple and irregular alterations (PSNR/SSIM/PSNR-HVS-M), (**a**) Kodak-1 (24.53/0.7417/21.94), (**b**) Kodak-3 (31.82/0.8959/29.27), (**c**) Kodak-11 (28.12/0.8670/26.08), (**d**) Kodak-14 (26.38/0.8263/23.41). For the PSNR-HVS-M metric, the highest values belong to [23; 24], followed by the proposed method, [36], and then by [2; 10]. A point worth mentioning is that the bit adjustment of SR-HTR and [36] negatively affects the results of PSNR-HVS-M due to the characteristics of this metric, as described in Tables 1 and 4. Furthermore, it is essential to notice that the methods [23; 24; 36] employ the 2-LSB method, and procedures [2; 10] use 3-LSB insertion. Additionally, methods [23; 24] do not exploit the total insertion capacity to use enough redundant information in the watermarks, leading to lower performance in the reconstruction stage. The second evaluation is related to change detection. For this test, _Precision_ and _Recall_ metrics were employed to compare the performance of the alteration schemes previously described. The _Precision_ results of this evaluation using the first alteration scheme are shown in Table 7. The best results belong to [2; 10]. Compared with the other methods, these methods possess an authentication scheme that generates multiple authentication bits for each block of \(n\times n\) pixels. Consequently, there is a higher likelihood to detect an alteration in a block because the number of bits to be compared increases. However, the proposed method was designed to generate a single authentication bit for each block of \(4\times 4\) pixels, and this significantly reduces the detection capability. Figure 12 illustrates the images utilized for the Precision and Recall comparison with the second alteration scheme, which considers the modification of multiple and irregular areas. Moreover, Table 8 shows the average Precision values of SR-HTR and the other state-of-the-art methods for the attacks given in Figure 12.  
Again, it can be observed that methods [2; 10] achieved a higher performance in this test by employing a more significant number of authentication bits. These results are followed by the method [24], then the designed SR-HTR, [36] and finally [23]. Nonetheless, the proposed SR-HTR method accomplished _Precision_ values higher than 0.9. It is further demonstrated that the novel SR-HTR method maintains a better balance between authentication and reconstruction capabilities.