# Data Hiding of Multicompressed Images Based on Shamir Threshold Sharing
## 4 Experimental Results  
At present, the performance metrics of image-based data hiding are mainly the Peak Signal to Noise Ratio (PSNR), Embedding Capacity (EC) and Embedding Rate (ER). The PSNR measures the distortion between the stego image (SI) and the original image (OI). The EC is the total number of bits of the secret message embedded in the cover image (CI). The ER is the ratio between the EC and the total number of pixels of the CI. There is conflict between the two indicators, namely, the PSNR and EC; that is, embedding more secret data often leads to aggravating image distortion. An excellent data hiding algorithm should ensure that there is no obvious visual difference between the SI and the CI, and try to embed a large amount of the secret message. The size of the images used in the experiments are standard grayscale images of \(512\times 512\), and the secret message is a randomly generated binary sequence. Figure 6 shows the original image (OI), the cover image (CI) after AMBTC compression, and the shadow image (SI) after embedding the secret message. There is almost no visual difference between the three sets of images. Table 1 shows the comparison of the PSNR between the OI and the CI, the OI and the SI, and the CI and the SI, under the threshold T = 10. Figure 7 and Table 2 show the PSNR of the covert image and the original image, the PSNR of the shadow image and the cover image, and the comparison of the embedding capacity under different thresholds, T = 5, T = 10, T = 15 and T = 20. It can be seen from the table that with the increase in T, there is only a slight decrease in the PSNR-SI. As can be seen from Table 1, the PSNR-CI is very close to the PSNR-SI, indicating that our embedding method has little effect on AMBTC decompressed images. Figure 6: Visual comparison of original image, cover image and shadow image. (**a**) Original Image, OI. (**b**) Cover Image, CI. (**c**) Shadow Image, SI. Figure 8 shows two sets of images with different smoothness; the first set of images has more embeddable blocks. The method proposed in this paper chooses to embed the subsecret messages segmented by the [PERSON] threshold scheme into the encoding of AMBTC of multiple different images. Since complex images have fewer embeddable blocks, it can be seen from Table 3 that there is a large difference in the amount of information embedded between smoother images and complex images, under the same threshold. The method proposed in this paper is more suitable for using smooth images as the cover image. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Image** & **PSNROI-CI** & **PSNROI-SI** & **PSNRCI-SI** & **EC** \\ \hline Airplane & 31.865 & 31.7193 & 46.5513 & \\ Baboon & 26.8191 & 26.6704 & 41.3761 & \\ Bridge & 28.3827 & 28.1893 & 41.8135 & \\ Man & 31.2594 & 30.9492 & 42.5611 & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of EC and PSNR of original image, cover image and shadow image. Figure 7: PSNR comparison of four test images under different thresholds. (**a**) Airplane. (**b**) Baboon. (**c**) Bridge. (**d**) Man. Table 4 shows the comparison results. Columns 6, 7 and 8 in the table give the embedding rate, storage volume and the PSNR of the shadow images, respectively. The methods in [20; 21; 22; 23; 24; 25] are dual-image data hiding methods, which generate two visually similar shadow images. As shown in Column 8, the PSNRs of the two shadow images