## 4 Experimental Results and Discussion
Encryption for AMBTC was performed for bitmap and two quantization levels, respectively. If only one of the bitmaps or the two quantization levels is encrypted, a part of the original image may remain in the encrypted image. Table 2 compares EC and PSNR according to the difference \(T\) between the two quantization levels. As the value of \(T\) decreases, EC decreases while PSNR increases. While, as the value of \(T\) increases, EC increases while PSNR deteriorates. In Table 2, it can be seen \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multirow{2}{*}{**Images**} & \multicolumn{2}{c}{**Cover AMBTC**} & \multicolumn{2}{c}{**Encrypted AMBTC**} & \multicolumn{2}{c}{**Decrypted AMBTC**} \\ \cline{2-7}  & **PSNR** & **SSIM** & **PSNR** & **SSIM** & **PSNR** & **SSIM** \\ \hline Barboon & 26.9765 & 0.8872 & 9.5038 & 0.0147 & 26.9757 & 0.887 \\ Barbara & 27.0756 & 0.9248 & 7.8847 & 0.0140 & 27.0702 & 0.923 \\ Boat & 31.5700 & 0.9388 & 8.9932 & 0.0146 & 31.5444 & 0.9355 \\ Goldhill & 32.8360 & 0.9208 & 9.0695 & 0.0159 & 32.8207 & 0.9196 \\ Airplane & 32.0372 & 0.9504 & 8.7070 & 0.0150 & 32.0017 & 0.9462 \\ Lena & 33.6556 & 0.9468 & 9.3058 & 0.0167 & 33.599 & 0.9423 \\ Pepper & 34.0968 & 0.9395 & 9.1550 & 0.0147 & 34.0397 & 0.9356 \\ Tifany & 35.6576 & 0.9473 & 6.8659 & 0.0140 & 35.5651 & 0.9426 \\ Zelda & 36.6537 & 0.9476 & 8.8716 & 0.0140 & 36.5378 & 0.9432 \\ Average & 32.3736 & 0.9337 & 8.6421 & 0.0153 & 32.2394 & 0.9306 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The PSNR and SSIM of the encrypted images and decrypted images when \(T=5\). that EC and PSNR were measured while increasing from \(T=5\) to \(T=20\). When \(T=5\), the average EC is 21,295 and the PSNR is 32.2393, which is high with an average of 32 dB. When \(T=10\), the average EC is 36,657 and the PSNR remains above 32 dB. When \(T=20\), the average EC was measured to be 48,336 and the PSNR was 29 dB, which can be seen to drop to less than 30 dB, but it shows a similar performance to the human visual system. In conclusion, if a block with a small difference between the two quantization levels is sufficient, not only can a large amount of data be hidden, but also the PSNR is excellent. This is affected by the characteristics of the image. Table 2 shows that it is difficult to hide a sufficient amount of data in the case of high-frequency images such as Baboon. In the case of a low-frequency image such as Pepper, since the difference between the two quantization levels in many blocks is relatively small, it is possible to hide a large amount of data while maintaining a high PSNR. Figure 5: Encryption results of the cover images: (**a**) Baboon, (**b**) Barbara, (**c**) Boat, (**d**) Goldhill, (**e**) Airplane, (**f**) Lena, (**g**) Peppers, (**h**) Tiffany, (**i**) Zelda. Table 3 compares [PERSON] et al. 's method of an AMBTC-based model with existing methods and our proposed method. Cover AMBTC is a criterion for evaluating performance, and a comparison of the PSNR can be conducted based on this criterion. PSNR\({}^{1}\) and PSNR\({}^{2}\) were obtained from the decrypted images and recovered images, respectively. Here, we measure PSNR\({}^{1}\) and PSNR\({}^{2}\) when \(T=5\). When hiding message bits in a bitmap, flip the bitmap from '0' to '1' or '1' to '0'. That is, when the difference between the two quantization levels is 1, the error occurring in this block is 1. If \(T=2\), the error is 2. In the end, if the value of \(T\) has increased, the amount of data to be hidden can be sufficiently increased, but the error will increase, the PSNR will deteriorate, and image damage will be large. Table 2 shows the EC and PSNR for the image while increasing the \(T\) value. Table 3 shows the simulation results for \(T=5\), where PSNR and EC were judged to be at appropriate levels. \(T=5\) was selected under the judgment that EC was at an appropriate level while minimizing PSNR. Comparing the payload of [PERSON] et al. 's with the payload of our proposed method, we demonstrated that the average payload of our proposed method is 20 times better.