## 4 Experimental Results and Discussion
Except for this, the performance is over 30 dB. When compressing the original image with AMBTC, since compression representing two quantization levels per block was used, the same level of performance as the original image was not observable, but as shown in Table 1, the SSIM was 0.9 or higher except for the case of Barboon. It can be seen that the characteristics of the original image are sufficiently reflected. In the case of restoring the original image by removing the error occurring for each block in the decoded image, it can be restored with the cover AMBTC shown in Table 1. In this way, it is expected that it is suitable for various applications because not only is the quality of the image sufficiently similar to that of the original image, but the compression can also be performed at a high level. Table 5 summarizes and compares the performance of the proposed method and the existing method. [PERSON] [12] proposed a method capable of extracting data without errors from the encrypted image, but there is a problem in the complete restoration of the original cover image. [PERSON] et al. 's method [13] and [PERSON] et al. 's method [19] achieved data extraction and complete restoration of the original cover image. However, both approaches require reserve space before hiding data. The method of [PERSON] et al. [22] maintained the block correlation of the image by using the histogram of the prediction error in the data embedding step and used the method of utilizing the extra space. This method also recovers the original image without errors using both keys. In [PERSON] et al. 's method [23], the RDH is based on the histogram modified embedding method, which is utilized for obtaining a high payload and low storage memory. [PERSON] et al. 's method [24] means that secret messages can be embedded by exploiting the redundant room derived from the quantization levels. Data hiding is then performed with the use of a labelling strategy. This method is an RDH method, which has already been verified. Therefore, there is no problem with restoring the original image. The method we proposed is a method that uses a Hamming code, has excellent data hiding performance and restored image quality, and it is also possible to restore the original cover image using this method. \begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Images** & **[PERSON] et al.’s (2018) [22]** & **[PERSON] et al. (2019) [23]** & **[PERSON] et al.’s (2020) [24]** & **Proposed** \\ \hline Baboon & 273 & - & 14,976 & 64,881 \\ Boat & 932 & 22,050 & 29,382 & 65,369 \\ Airplane & 1365 & 23,610 & 34,564 & 65,013 \\ Lena & 1270 & 22,287 & 36,418 & 65,329 \\ Barbara & 524 & - & 13,644 & 62,945 \\ Peppers & 926 & 22,142 & 41,080 & 64,929 \\ Average & 881 & 22,522 & 28,344 & 64,744 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of maximum EC between our scheme and previous schemes. Figure 6: Comparison of quality of images recovered from encrypted images: (**a**) [PERSON], (**b**) Barbara, (**c**) Boat, (**d**) Goldhill, (**e**) Airplane, (**f**) Lena, (**g**) Peppers, (**h**) Tiffany, (**i**) Zelda. \begin{table}
\begin{tabular}{l c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{4}{c}{**Criterion**} \\ \cline{2-5}  & \multicolumn{2}{c}{**Separable**} & \multicolumn{2}{c}{**Error in Extracted Data**} & \multicolumn{2}{c}{**Error in Reconstructed**} & \multirow{2}{*}{**Embedding Efficiency**} \\  & \multicolumn{2}{c}{**Cover Image**} & & & \\ \hline [PERSON] et al.’s [13] & O & X & X & Mid \\ [PERSON]’s [12] & X & X & O & Low \\ [PERSON] et al.’s [19] & O & X & X & Low \\ [PERSON] et al.’s [22] & O & X & O & High \\ [PERSON] et al.’s [23] & O & X & O & High \\ [PERSON] et al.’s [24] & O & X & O & High \\ Proposed & O & X & O & High \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Performance comparison among previous schemes and proposed scheme.