# Hybrid Data Hiding Based on AMBTC Using Enhanced Hamming Code
## 4 Experimental Results
In Figure 9, the curves of our proposed method and the two existing methods (i.e., [PERSON] and [PERSON] and [PERSON]) are similar, while [PERSON] and [PERSON]'s histogram curve has a larger amplitude than the other methods. The reason is that the maximum EC of [PERSON] and [PERSON]'s method is up to 150,000 bits. In other words, we can see that the quality of the image reaches the lower limit because it exhausts all possible resources. The histogram does not show much difference because our proposed method and the two existing methods keep more than 33 dB in common when concealing 150,000 bits. As shown in Figure 8, as the EC increases, the histogram of the stego image also is far from the histogram of the original cover image. Table 2 shows an experiment to compare the PSNR and SSIM after concealing the same amount of data (120,000 bits) in the cover image for a more objective performance check and reliable comparison. The SSIM of the proposed method shows the highest value. On the other hand, in the case of the  
Figure 9: Compared histograms among the proposed method and other related methods with the Lena image when the number of hidden bits is 150,000. PSNR, [PERSON]'s method [33] shows a high average. In fact, the PSNR only quantifies the quality of reconstructed or damaged images in relation to the facts. For this reason, we introduce SSIM as a criterion for the secondary evaluation. SSIM evaluates the structure of the image. The SSIM of the reconstructed image for the ground image is always one, and if the value is close to one, you can see that the image quality is excellent. Therefore, we can see that our proposed method is superior to the existing methods in terms of SSIM. Table 3 shows the MSE and NCC simulation results for the existing and proposed methods for the four images. The average MSE value of the proposed method is lower than those of the three other methods. The MSE value of the Airplane image in our proposed method is slightly higher than those of [PERSON] and [PERSON] [29] and [PERSON] [33]. However, from the NCC scores, there is no difference, so it is objectively proven that there is no problem with the performance of our proposed method. Furthermore, when the maximum EC of [PERSON] and Sun reaches 270,000 bits, the PSNR drops to 23 dB. On the other hand, our proposed method can maintain the PSNR higher than 30 dB, so the DH performance of our proposed method is useful. Our proposed method can obtain better performance by creating a lookup table to obtain more optimal values than [PERSON]'s method. Table 4 shows the comparison of the CPU execution time between the proposed and the existing methods. The computer for the experiment is a YOGA 730, and the CPU processor is Intel(R) Core(TM) i5-8250U CPU 1.6 GHz. The software is MATLAB R2019a. Here, we measure the CPU time to conceal a random number from 20,000 bits to 200,000 bits in the Lena image by using the four methods (i.e., [PERSON] and [PERSON], [PERSON], [PERSON] and [PERSON], our proposed method). The process of the measurement includes AMBTC compression, data embedding, and AMBTC decompression. The most time-consuming method is that of [PERSON] and [PERSON], and the least time-consuming method is that of [PERSON] and [PERSON]. The method we propose is faster than [PERSON] and [PERSON]'s, but it is time consuming compared to the other two. However, if we code using the C language, the required time would be less than 1 s.