# Frequency-Based Adaptive Interpolation Filter in Intra Prediction
## 4 Experimental Results
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Sequence**} & \multicolumn{6}{c}{**All Intra Main 10**} \\ \cline{2-7}  & \multicolumn{2}{c}{**Method C**} & \multicolumn{2}{c}{**Method D**} \\  & **Y** & **Cb** & **Cr** & **Y** & **Cb** & **Cr** \\ \hline Class A1 & \(0.01\%\) & \(-0.18\%\) & \(0.05\%\) & \(\mathbf{-0.09\%}\) & \(-0.10\%\) & \(-0.02\%\) \\ Class A2 & \(0.02\%\) & \(0.08\%\) & \(0.00\%\) & \(0.00\%\) & \(0.04\%\) & \(-0.04\%\) \\ Class B & \(0.01\%\) & \(0.09\%\) & \(0.01\%\) & \(0.01\%\) & \(0.02\%\) & \(0.05\%\) \\ Class C & \(\mathbf{-0.40\%}\) & \(-0.22\%\) & \(-0.36\%\) & \(0.01\%\) & \(0.03\%\) & \(0.02\%\) \\ Class D & \(\mathbf{-0.30\%}\) & \(-0.25\%\) & \(-0.23\%\) & \(-0.01\%\) & \(-0.06\%\) & \(0.08\%\) \\ \hline Overall & \(\mathbf{-0.14\%}\) & \(-0.09\%\) & \(-0.11\%\) & \(-0.01\%\) & \(-0.01\%\) & \(0.03\%\) \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Experimental results of method C and method D based on frequency-based adaptive filter selection method. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Sequence**} & \multicolumn{6}{c}{**All Intra Main 10**} \\ \cline{2-7}  & \multicolumn{2}{c}{**Method A**} & \multicolumn{2}{c}{**Method B**} \\  & **Y** & **Cb** & **Cr** & **Y** & **Cb** & **Cr** \\ \hline Class A1 & \(0.01\%\) & \(-0.06\%\) & \(0.06\%\) & \(\mathbf{-0.08\%}\) & \(-0.20\%\) & \(-0.15\%\) \\ Class A2 & \(0.02\%\) & \(-0.03\%\) & \(-0.02\%\) & \(-0.01\%\) & \(0.00\%\) & \(-0.04\%\) \\ Class B & \(-0.01\%\) & \(0.04\%\) & \(-0.01\%\) & \(-0.01\%\) & \(0.05\%\) & \(-0.05\%\) \\ Class C & \(\mathbf{-0.33\%}\) & \(-0.22\%\) & \(-0.27\%\) & \(0.00\%\) & \(-0.02\%\) & \(0.07\%\) \\ Class D & \(\mathbf{-0.28\%}\) & \(-0.32\%\) & \(-0.15\%\) & \(-0.01\%\) & \(-0.07\%\) & \(0.03\%\) \\ \hline Overall & \(\mathbf{-0.13\%}\) & \(-0.12\%\) & \(-0.08\%\) & \(-0.02\%\) & \(-0.03\%\) & \(-0.02\%\) \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Experimental results of Method A and Method B. The increases in percent selections of 4-tap SIF and 8-tap DCT-IF result in BD rate gains in Table 12. The use of 4-tap SIF with low LPF characteristics and 8-tap DCT-IF with strong HPF characteristics in line with _high_freq_ratio_ with small CU helps to increase the BD rate in the proposed method. Moreover, the use of 8-tap SIF with strong LPF characteristics and 4-tap DCT-IF with weak HPF characteristics according to _high_freq_ratio_ at a large CU helps to slightly increase the BD rate in the proposed method. For _nTb5_ > 4, 4-tap DCT-IF is only applied to CUs using the MRL or ISP tool in the VVC anchor. However, 8-tap DCT-IF and 4-tap SIF based on _high_freq_ratio_ are applied to \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline  & \multicolumn{10}{c}{**All Intra Main 10**} \\ \hline \multirow{3}{*}{**H**} & \multirow{3}{*}{**W**} & \multirow{3}{*}{**VVC Anchor**} & \multirow{3}{*}{**VVC Anchor with MRL and ISP**} & \multicolumn{6}{c}{**Adaptive Filter Method Based on**} \\  & & & & & & **VVC Anchor with MRL and ISP**} & \multicolumn{6}{c}{**high_freq_ratio**} \\  & & & **4** & **8** & **16** & **32** & **64** & **4** & **8** & **16** & **32** & **64** & **8** & **16** & **32** & **64** \\ \hline
4 & 100.00 & 100.00 & 85.67 & 94.70 & — & 100.00 & 100.00 & 82.25 & 89.16 & — & 97.16 & 95.80 & 91.11 & 97.27 & — \\
8 & 100.00 & 87.89 & 81.99 & 25.68 & — & 100.00 & 91.35 & 81.42 & 44.36 & — & 96.77 & 91.36 & 86.69 & 53.43 & — \\
16 & 87.38 & 83.20 & 8.32 & 17.24 & — & 86.26 & 82.59 & 19.35 & 27.85 & 100.00 & 92.62 & 86.76 & 19.83 & 33.13 & 0.04 \\
32 & 94.01 & 19.98 & 14.73 & 0.00 & — & 90.45 & 36.35 & 23.17 & 10.59 & — & 97.06 & 42.55 & 27.34 & 0.07 & — \\
64 & — & — & — & — & 0.00 & — & — & 100.00 & — & 5.56 & — & — & 0.07 & — & 0.07 \\ \hline \hline \end{tabular}
\end{table} 
Table 11: CUs percentage using DCT-IF in which H and W are the height and width of each CU.