# Robust JND-Guided Video Watermarking via Adaptive Block Selection and Temporal Redundancy
## 4 Experimental Results
### Evaluation Under Attacks  
In order to assess the real-world applicability of the proposed watermarking scheme, we conducted a systematic evaluation of its robustness under a diverse set of common video impairments. This type of analysis is critical in watermarking research, as any practical solution must not only be imperceptible and efficient, but also resilient against typical transformations that video content undergoes during distribution, editing, compression, or playback. While the previous experiments demonstrated the method's imperceptibility and robustness in ideal conditions, the current section focuses on how the proposal performs under actual distortion, without access to the original unmodified content. Four categories of attacks were selected for this evaluation, each simulating a distinct class of degradation. First, Gaussian noise (\(\mu=0\), \(\sigma^{2}=0.05\)) was added to the whole frames, emulating noise, re-encoding errors, or transmission artifacts. Second, video compression was applied using two widely used lossy codecs: H.264 (configured at CRF 28) and VP8 (quality level 30). These attacks simulate bandwidth-constrained streaming or export operations. Finally, a temporal desynchronization attack was performed by shifting watermark extraction indices randomly by \(\pm 3\) frames, simulating situations where scenes are edited, frames are dropped, or timing variations occur during decoding or rendering. The results, summarized in Table 5, reveal consistent robustness of the proposed watermarking system across all attack scenarios and video resolutions. Under Gaussian noise, the average BER remained low (0.6% for CIF, 1.1% for 4 CIF, and 1.4% for HD), with SSIM degradation below 0.086 and PSNR loss under 7 dB. These results confirm that the adaptive quantization mechanism distributes watermark energy in structurally rich regions where random noise has limited perceptual impact. In the case of video compression, H.264 was more aggressive than VP8, particularly for HD content where the BER reached 1.8% and SSIM dropped by 0.174. However, even in this setting, recovery accuracy remained above 98.6% and VMAF degradation stayed within tolerable bounds. Please note that in typical H.264 compression using FFmpeg and the libx264 encoder, a CRF value of 28 relates to a relevant compression level, yielding an average bitrate between 800 and 1500 kbps for CIF and 4 CIF video content, and 1.5 to 3 Mbps for HD content, depending on motion complexity and scene variability. In VP8 compression, the parameter Q refers to the target constant quantizer value, with a range between 4 (high quality) and 63 (maximum compression). A setting of Q = 30 corresponds to moderate-to-high compression, typically resulting in bitrates between 600 and 1200 kbps for CIF and 4 CIF videos, and 1-2 Mbps for HD content. Actual bitrate depends on frame complexity and motion, as VP8 is a variable bitrate codec. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Strategy** & **BER (\%)** & **VMAF** & **Avg. Sync Error** \\ \hline Random Frame Insertion & 2.7 & 89.7 & 1.8 \\ Scene-Based Insertion & 0.3 & 95.2 & 0.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of BER and VMAF for multiframe insertion strategies. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Attack Type**} & \multicolumn{5}{c}{**BER \%**} & \multirow{2}{*}{**SSIM Drop**} & \multirow{2}{*}{**PSNR Drop**} & \multirow{2}{*}{**VMAF Drop**} \\ \cline{2-2} \cline{5-6}  & **CIF** & **4 CIF** & & & & \\ \hline Gaussian noise & 0.6 & 1.1 & 1.4 & 1.03 & 0.085 & 6.8 & 10.5 \\ H.264 Compression (CRF 28) & 0.9 & 1.5 & 1.8 & 1.40 & 0.120 & 10.3 & 16.2 \\ VP8 Compression (Q = 30) & 0.7 & 1.4 & 1.7 & 1.26 & 0.098 & 9.2 & 14.9 \\ Temporal Desync (\(\pm\)3 frames) & 0.7 & 1.2 & 1.5 & 1.13 & 0.094 & 7.9 & 11.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Watermark robustness under common video attacks.