6. Conclusions and future work

with 1% density. At the receiving side, the videos were denoised using the selective filter; then the watermarks were extracted. Figure 21 shows the normalized correlations and the PSNRs under these conditions. It is clear that the selective filtering scheme enhanced the visual appearance by eliminating the noise without significant effects on the efficiency of the watermarking process. Furthermore, Figure 22 shows the results when 2D median filter is used. It can be seen that our selective denoising filter outperformed the 2D median filter in terms of the correlation

The performance of the watermarking process with the use of the proposed selective filter where the blue line is

The performance of the watermarking process with the use of a 2D median filter where the blue line is the

The watermarking process response to false alarm test, the right watermark is the 350th with different videos:

(a) Akiyo, (b) Foreman, (c) Football, (d) BasketballDrill, and (e) BasketballDrive.

Figure 21.

Figure 22.

Figure 23.

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the correlation and the green line is the PSNR.

Wavelet Transform and Complexity

correlation and the green line is the PSNR.

This work proposes a DWT-based watermarking process using randomly generated orthonormal filter banks. An enhanced detection process was proposed to add to the robustness of the system. Moreover, a selective filtering process was developed to eliminate the noise. A good deal of the security of the system was achieved by the randomness in the filter banks, the pseudorandom sequence that was used to encode the watermark, and the regions of hidings. It was shown that the proposed technique performs well with and without HEVC. The compression ratio that was used is typical. Further investigation of the efficiency of the watermarking process under other aggressive attacks will be discussed and researched in future work. Moreover, an integration process of the data hiding process inside videos and the HEVC process will be studied and investigated.
