# Research on VVC Intra-Frame Bit Allocation Scheme Based on Significance Detection
## 4 Results
### Experimental Condition
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Sequences** & **Target Bitrate** & **VTM 14.0** & **Proposed** & \(\Delta\)**PSNR** \\  & & **RC Y-PSNR** & **Method Y-PSNR** & \\ \hline PeopleOnStreet & 12,000 & 32.8213 & 32.8479 & 0.0266 \\  & 30,000 & 37.4595 & 37.4576 & \(-\)0.0019 \\  & 40,000 & 38.9225 & 38.9233 & 0.0008 \\  & 50,000 & 40.1155 & 40.1172 & 0.0017 \\ BasketballDrive & 1500 & 31.9553 & 31.899 & \(-\)0.0563 \\  & 2000 & 33.0822 & 33.1002 & 0.018 \\  & 2500 & 33.9155 & 33.9622 & 0.0467 \\  & 3000 & 34.6552 & 34.6369 & \(-\)0.0183 \\ BQMall & 20,000 & 40.4325 & 40.4504 & 0.0179 \\  & 30,000 & 42.6537 & 42.7425 & 0.0888 \\  & 40,000 & 44.5173 & 44.5839 & 0.0666 \\  & 50,000 & 45.8516 & 46.002 & 0.1504 \\ Race Horses & 5000 & 42.7031 & 42.7139 & 0.0108 \\  & 8000 & 46.2087 & 46.3002 & 0.0915 \\  & 10,000 & 47.5341 & 47.6092 & 0.0751 \\  & 12,000 & 48.8587 & 49.1383 & 0.2796 \\ FourPeople & 5000 & 35.0326 & 34.9933 & \(-\)0.0393 \\  & 6000 & 36.0668 & 36.1002 & 0.0334 \\  & 8000 & 37.7986 & 37.8055 & 0.0069 \\  & 10,000 & 39.1359 & 39.139 & 0.0031 \\ BasketballDrillText & 2000 & 31.6835 & 31.8176 & 0.1341 \\  & 4000 & 34.928 & 34.9855 & 0.0575 \\  & 6000 & 36.8878 & 36.9174 & 0.0296 \\  & 8000 & 38.2579 & 38.3774 & 0.1195 \\ Average & & & & 0.05 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: PSNR Comparison Results. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Sequences** & **Target Bitrate** & **VTM14.0 RC** & **Bit Error (\%)** & **Proposed Method** & **Bit Error (\%)** \\ \hline BQMall & 20,000 & 19,884.96 & 0.575 & 20,017.9 & 0.090 \\  & 30,000 & 28,863.36 & 3.789 & 29,267.5 & 2.442 \\  & 40,000 & 39,685.92 & 0.785 & 40,003.7 & 0.009 \\  & 50,000 & 47,296.32 & 5.407 & 48,072.5 & 3.855 \\ Race Horses & 5000 & 4780.8 & 4.384 & 4742.64 & 5.147 \\  & 8000 & 7029.12 & 12.136 & 7042.08 & 11.974 \\  & 10,000 & 7925.52 & 20.745 & 7985.04 & 20.150 \\  & 12,000 & 8960.16 & 25.332 & 9168.96 & 23.592 \\ FourPeople & 5000 & 5086.08 & 1.722 & 5042.4 & 0.848 \\  & 6000 & 6011.52 & 0.192 & 6025.44 & 0.424 \\  & 8000 & 7919.52 & 1.006 & 7932.48 & 0.844 \\  & 10,000 & 9825.12 & 1.749 & 9845.76 & 1.542 \\ BasketballDrillText & 2000 & 1942.8 & 2.86 & 1978.4 & 1.080 \\  & 4000 & 3705.6 & 7.36 & 3728.8 & 6.780 \\  & 6000 & 5555.6 & 7.407 & 5584 & 6.933 \\  & 8000 & 7348.4 & 8.145 & 7494.8 & 6.315 \\ Average & & & 4.49 & & 4.037 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: _Cont._compared with the default algorithm. At the same time, due to the nature of the default bit allocation algorithm, which allocates the remaining CTUs at the remaining bit cost, the CTUs at the end of the frame will have fewer CTUs to allocate, and a more balanced situation is reached, which is characterized by much less than 0 in the image. In Table 5, although the error is higher than the default algorithm in some conditions, most of the results are better than the default algorithm, which reduces the error from 4.49% to 4.037% on average; similarly, the average Y-PSNR is improved by 0.05 dB in Table 6. Most of the data in Table 6 performs well, but there are still some negatively optimized data, such as when the cost is 30,000 kbps in PeopleOnStreet, when the cost is 1500 and 3000 kbps in the BasketballDrive sequence, and so on. After our analysis, the reason for this phenomenon is partly due to the characteristics of the sequences; sequences similar to the PeopleOnStreet and BasketballDrive categories have complex content and fast movement of the character scenes, and therefore are more difficult to encode, which may lead to similar situations; and secondly, it may be due to the fact that fewer combinations of parameters were used to determine the optimal tuning multiplicity for each test sequence. Secondly, this may be due to the fact that the combination of parameters used to determine the optimal adjustment multiplier for each test sequence was small, and not entirely precise to the combination that would give the best results, so this phenomenon may be elaborated.