# High-Quality Video Watermarking Based on Deep Neural Networks for Video with HEVC Compression +
## 5 Conclusions  
Embedding a watermark in a video, taking into account maximizing the accuracy of the watermarked image in relation to the original image under the compression conditions introduced by the video codec, is a complex issue. For solutions using DNNs, it is worth considering the required hardware resources for DNN training and their subsequent use. The solution presented in this publication allows the DNN to operate natively for a 128 \(\times\) 128 image to be freely scaled to larger images through the use of a sliding window, which also allows for a potential increase in watermark capacity within a single video frame. Compression introduced by HEVC above a CRF of 16 is more challenging for the encoder and decoder training process for the purposes of watermark embedding and recovery. This state of affairs is due to the complex HEVC compression characteristics. Appropriate implementation of the training process by introducing an additional training element, the DNN coder, which mimics the HEVC compression channel, accelerates convergence at the training of HEVC compression characteristics, which enables the encoder and decoder to operate at higher compression values. The presented method takes into account not only HEVC compression but also the image compression introduced through the application of YUV420p. The use of the YUV color model in the YUV420p variant further affects the compression of the image and therefore reduces the size of the output video file, however, it is also an additional issue to consider when embedding the watermark. The issue presented in the previous sentence is solved through ASPA, which allows the size of the image fragment used to store the watermark bit string to be selected. By applying synergies in the application of ASPA and HEVC compression together with YUV420p in the form of the appropriate use of the subsquares present in these components of the method under discussion, it is possible to correctly embed and recover the watermark despite a fourfold reduction in capacity for chrominance through the application of YUV420p. The analysis of the results of the conducted tests of the proposed method confirms the possibility of completely recovering the watermark from a single frame in terms of changes in the value \(\langle 0;22\rangle\) of the compression coefficient determined by the CRF. It is also possible to completely recover the watermark from individual video frames for CRF values not exceeding 24, however, it is more probable that for decoded watermark, BER would not be 0. Further research is needed into the possibility of more accurate reproduction of an image with embedded watermarked compared to the original. The issues of increasing the capacity of the watermark itself and increasing its resistance to changes in its carrier while reducing the time required for embedding would also require further exploration. In order to improve the coefficients describing the accuracy of the reproduction of the embedded watermarked image to the original image, the error function used during the training process should be further modified alongside the performance improvement of mimicking the HEVC compression by the DNN coder, which is the training element of the H.265 codec characteristics for encoder and decoder. Further increases in watermark capacity can be achieved by modifying the ASPA parameters. The application of an additional element, in the form of a variable decoder extension dedicated to different types of interference, will improve the correctness of watermark recovery from a carrier subjected to various watermark distorting operations. The introduction of ECC schemes for ASPA purposes will increase the probability of full watermark recovery. Another possibility to improve the performance of the decoder subsystem is to use the video frame sequence with a histogram calculation to map most of the repeated values between frames at the output of the DNN decoder, enhancing the watermark recovery.