# High-Quality Video Watermarking Based on Deep Neural Networks for Video with HEVC Compression +
## 4 Results
### Watermarking Research Results
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Frame \#** & **CRF 0** & **CRF 7** & **CRF 12** & **CRF 16** & **CRF 20** & **CRF 22** & **CRF 23** & **CRF 24** & **CRF 25** \\ \hline  & AVG 1: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0536 & AVG: 01518 \\
1 & COM 2: 0 & COM: 0 & COM: 0 & COM: 0 & COM: 0 & COM: 0 & COM: 0.0804 & COM: 0.0714 & COM: 0.2143 & COM: 0.3571 \\  & MED 3: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0.0179 & MED: 0.0625 \\  & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0.089 & AVG: 0.0089 & AVG: 0.1071 \\
5 & COM: 0 & COM: 0 & COM: 0 & COM: 0 & COM: 0.0357 & COM: 0.0447 & COM: 0.0893 & COM: 0.25 & COM: 0.2589 \\  & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0.0089 & MED: 0.0089 & MED: 0.0536 \\  & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0.0089 & AVG: 0.0089 & AVG: 0.0161 \\
10 & COM: 0 & COM: 0 & COM: 0 & COM: 0 & COM: 0.0179 & COM: 0.0357 & COM: 0.1429 & COM: 0.2679 & COM: 0.4821 \\  & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0.0446 \\  & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0.0089 & AVG: 0.0089 & AVG: 0.0265 & 0.1875 \\
15 & COM: & COM: 0 & COM: 0 & COM: 0 & COM: 0.0179 & COM: 0.0804 & COM: 0.2768 & COM: 0.3482 & COM: 0.4464 \\  & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0.0899 & MED: 0.0899 & MED: 0.0714 \\  & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0.0899 & AVG: 0.0714 & AVG: 0.2143 \\
20 & COM: 0 & COM: 0 & COM: 0 & COM: 0 & COM: 0.0714 & COM: 0.1429 & COM: 0.25 & COM: 0.4375 & COM: 0.5 \\  & MED: 0 & MED:0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0.0899 & MED: 0.0899 & MED: 0.1071 \\  & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0.0179 & VOF: 0.0737 & VOF: 0.0357 & VOF: 0.2321 \\
25 & COM: 0 & COM: 0 & COM: 0 & COM: 0 & COM: 0.0179 & COM: 0.01161 & COM: 0.3839 & COM: 0.3839 & COM: 0.3571 \\  & MED: 0 & MED:0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0.0899 & MED: 0.0893 & MED: 0.0893 \\  & MED: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0 & AVG: 0.0179 & VOF: 0.0714 & VOF: 0.1607 \\
30 & COM: & COM: 0 & COM: 0 & COM: 0 & COM: 0.0179 & COM: 0.0804 & COM: 0.2768 & COM: 0.3482 & COM: 0.4464 \\  & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0.0899 & MED: 0.0714 & VOF: 0.0714 \\  & MED: & 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0.0899 & MED: 0.0714 & VOF: 0.0714 \\
20 & COM: & COM: 0 & COM: 0 & COM: 0 & COM: 0.0179 & COM: 0.0804 & COM: 0.2768 & COM: 0.3482 & COM: 0.4464 \\  & MED: & 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0 & MED: 0.0899 & MED: 0.0714 & VComparing the results in Tables 7 and 8, there is an obvious reduction in image accuracy for the different HEVC compression values related to changes in the image created during the embedding process of the watermark. The change in carrier reproduction quality is more pronounced for low compression values and decreases as compression increases. This is due to the fact that DNN encoder was trained to embed the watermark under higher compression conditions. Besides calculating MSE and PSNR coefficients, the quality of embedded video image frames in comparison to original frames was additionally assessed visually by an independent test group. The objective of the test was to compare embedded images (video frames) with their original counterpart. The tested person did not know which image was embedded and which was original. Every tested person was given 7 pairs of images. The objective of the tested person was to point out which image is original or asses pair as the same images. The formula to calculate the quality of the algorithm is given below:  
\[Q=\frac{L}{N}\cdot 100\% \tag{21}\]  
where \(Q\) is the subjective assessment of the quality of the encoded image, \(L\) is the number of pairs of pictures identified as being the same or misclassified, \(N\) is the number of image pairs. Figure 8: PSNR of the embedded watermarked image relative to the original image.