# Keyframe Insertion: Enabling Low-Latency Random Access and Packet Loss Repair
## 4 Results
### Impact on Quality
#### 4.3.5 Worst-Case Quality Decrease  
Although the average VMAF, PSNR, and SSIM decreases remain relatively small, it is important to carefully monitor the worst-case quality decrease in a single frame of  
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline  & & \multicolumn{6}{c}{**Average PSNR Decrease (dB)**} \\ \cline{3-8}
**QP\({}_{\text{CS}}\)** & & \multicolumn{2}{c}{**K\({}_{\text{ISrc}}\)**} & \multicolumn{2}{c}{**K\({}_{\text{INS}}\)**} & \\ \hline  & **QP\({}_{\text{NS}}\)** = & **22** & **27** & **32** & **37** & **22** & **27** & **32** & **37** \\ \hline
22 & & 0.34 & 0.18 & 0.10 & 0.03 & **0.24** & 0.15 & 0.06 & 0.05 \\
27 & & 0.61 & **0.32** & 0.13 & 0.06 & 0.58 & **0.22** & 0.12 & 0.05 \\
32 & & 1.29 & 0.66 & **0.29** & 0.14 & 1.26 & 0.70 & **0.19** & 0.10 \\
37 & & 2.41 & 1.35 & 0.62 & **0.32** & 2.46 & 1.30 & 0.65 & **0.19** \\ \hline \hline \end{tabular}
\end{table}
Table 4: Average decrease in Peak Signal-to-Noise Ratio (PSNR).  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline  & & \multicolumn{3}{c}{**Frames Before Quality Inversion**} \\
**QP\({}_{\text{CS}}\)** & **QP\({}_{\text{NS}}\)** = & **22** & **27** & **32** & **37** \\ \hline
22 & & 6.1 & 40.9 & 121.1 & 158.9 \\
27 & & 57.3 & **15.8** & 117.7 & 160.7 \\
32 & & 13.7 & 94.0 & **46.4** & 160.6 \\
37 & & 51.6 & 44.3 & 118.1 & **143.5** \\ \hline \hline \end{tabular}
\end{table}
Table 3: Average number of frames (after keyframe insertion) where \(\text{K}_{\text{src}}\) has a better VMAF score than \(\text{K}_{\text{INS}}\). Thereafter, \(\text{K}_{\text{INS}}\) has a better VMAF score than \(\text{K}_{\text{src}}\) for the first time.  
\begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline  & & \multicolumn{6}{c}{**Average SSIM Decrease**} \\
**QP\({}_{\text{CS}}\)** & & \multicolumn{6}{c}{**K\({}_{\text{ISrc}}\)**} & \multicolumn{6}{c}{**K\({}_{\text{INS}}\)**} \\ \hline  & **QP\({}_{\text{NS}}\)** = & **22** & **27** & **32** & **37** & **22** & **27** & **32** & **37** \\ \hline
22 & & 0.05 & 0.06 & 0.03 & \(-\)0.09 & **0.04** & 0.06 & 0.04 & 0.03 \\
27 & & 0.09 & **0.10** & 0.  
a single tested sequence as well. As the keyframe insertion introduces errors that can drift uncontrollably, the worst-case results may expose obtrusive artefacts. For example, Figure 6 shows the VMAF decrease of \(\text{KI}_{\text{src}}\) compared to \(\text{NS}_{\text{src}}\), for all sequences, with \(\text{QP}_{\text{NS}}=\text{QP}_{\text{CS}}=22\). Although the VMAF decrease of most tested sequences stabilize between 0 and 1 VMAF point, the _BQSquare_-sequence has a VMAF decrease of up to 4.3 VMAF points. This worst-case sequence is discussed more thoroughly in Section 4.4.  
On a higher level, Table 6 shows the worst-case VMAF score decrease for both \(\text{KI}_{\text{src}}\) and \(\text{KI}_{\text{NS}}\), for all \(\text{QP}_{\text{NS}}\), and for all \(\text{QP}_{\text{CS}}\). More specifically, each value in the table was calculated by taking the maximum VMAF decrease over all frames and all tested sequences.  
In general, the worst-case VMAF score decrease results are approximately an order of magnitude higher than the average results in Table 2. Additionally, the contrast between \(\text{KI}_{\text{src}}\) and \(\text{KI}_{\text{NS}}\) is even more pronounced. That is, the worst cases of \(\text{KI}_{\text{src}}\) are generally much larger than those of \(\text{KI}_{\text{NS}}\).