# Texture-Guided Graph Transform Optimization for Point Cloud Attribute Compression
## 4 Experimental Results
### Compression Performance Evaluation  
Table 3 presents an overview of the compression performance evaluation, comparing the proposed scheme with competitive platforms G-PCC PLT, G-PCC RAHT, and BAAC in point cloud attribute lossy compression. In Table 3, we utilize the BD-BR value to quantify the average bitrate reduction achieved by our proposed scheme compared to comparative methods at four testing bitrate points. A negative BD-BR value indicates a reduction in bitrate, implying improved compression efficiency. Compared to G-PCC PLT, our scheme achieves average BD-BR gains of 15.81%, 30.28%, and 29.57% on coding Y, U, and V components, respectively. Similarly, compared to G-PCC RAHT, we observe average BD-BR gains of 31.02%, 30.71%, and 32.14% on Y, U, and V components, respectively. Notably, while G-PCC PLT and G-PCC RAHT represent attribute codecs in the latest standard point cloud compression platform MPEG G-PCC(v23), our scheme significantly improves attribute coding performance over G-PCC by integrating a well-designed graph transform coding tool. When compared with the graph transform anchor BAAC, our scheme achieves average BD-BR gains of 16.24%, 19.59%, and 20.44% on coding Y, U, and V components, respectively. The results denote that when equivalent reconstruction quality is achieved, our scheme can realize bitrate savings of 16.24%, 19.59%, and 20.44% on coding Y, U, and V components in comparison to BAAC. These bitrate savings are indeed crucial, as they directly translate into reduced point cloud storage requirements and transmission bandwidth. This performance enhancement over BAAC is achieved by leveraging texture-guided priors in the joint rate-distortion-sparsity optimization process for graph construction. Unlike BAAC, which solely relies on geometry information for graph construction, our scheme transcends such limitations, resulting in superior coding performance improvement. The consistent and substantial attribute BD-BR gains obtained by our scheme across all tests underscore its effectiveness and robustness in compressing point clouds with diverse attribute features. These findings consistently validate the superior coding efficiency of our approach for point cloud attribute compression. Since the experimental tests are conducted at different bitrate points for point cloud attribute lossy compression, presenting compression ratios alone in Table 3 may not adequately reflect the degree of attribute coding distortion. As shown in Figure 4, we provide the results of the total attribute bitrates and combined PSNR values at each testing bitrate  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Category** & **Sequence** & **Abbreviation** & \begin{tabular}{c} **Total Point** \\ **Number** \\ \end{tabular}  & \begin{tabular}{c} **Geometry** \\ **Precision** \\ \end{tabular}  & **Attribute Type** \\ \hline Solid & \begin{tabular}{c} Basketball\_player\_vox11\_00000200 \\ Dancer\_vox11\_0000001 \\ Longdress\_vox10\_1300 \\ Loot\_vox10\_1200 \\ Redandblack\_vox10\_1550 \\ Soldier\_vox10\_0690 \\ Thailandancer\_vawdeep\_vox12 \\ Queen\_0200 \\ Facade\_00064\_vox11 \\ \end{tabular}  & \begin{tabular}{c} Basketball\_2,925,514 \\ Dancer 2,592,758 \\ Dancer 2,592,758 \\ Londress\_vox10\_1300 \\ Loot 805,285 \\ Redandblack\_vox10\_1550 \\ Soldier\_vox10\_0690 \\ Thailandancer\_v \\ Staence\_0200 \\ Facade\_00064\_vox11 \\ \end{tabular}  & \ \begin{tabular}{c} Basketball\_2,925,514 \\ Dancer 2,592,758 \\ Dancer 2,592,758 \\ Londress\_vox10\_1300 \\ Loot 805,285 \\ Redandblack\_vox10\_1550 \\ Soldier\_vox12 \\ Soldier\_vawdeep\_vox12 \\ Boxer\_vox12 \\ \end{tabular}  &
\begin{tabular}{c} 11 \\ Dancer 2,592,758 \\ Londress\_vox10\_1300 \\ Loot 805,285 \\ Redandblack\_vox1550 \\ Redandblack\_vox1550 \\ Redandblack\_vox1550 \\ Redandblack\_vox1550 \\ Redandblack\_vox1550 \\ Redandblack\_vox1550 \\ Redandblack\_vox1550 \\ Redandblack\_vox1550 \\ Redandblack\_v1550 \\ Redandblack  
point of the proposed scheme and comparative platforms.