研究点云编码中几何与属性比特率分配的权衡，发现多分给属性更好。
Quality Analysis of the Coding Bitrate Tradeoff Between Geometry and Attributes for Colored Point Clouds
- 用不同比特率比例（30%/70%到70%/30%）测试点云压缩效果。
- 在五组测试中，属性多分比特率时重建质量略优。
- 适合关注点云压缩效率与视觉质量平衡的研究者。
通常点云编码器对几何和属性（如RGB颜色）分配相似比特率。本文研究了几何与属性间不同比特率分配对质量的影响。使用MPEG标准的几何点云压缩（G-PCC）对五类具有不同特征的点云进行编码，几何部分采用八叉树，属性部分使用区域自适应分层变换和预测提升变换。同时测试了JPEG Pleno点云验证模型。考虑了五种比特率分配方案：70%/30%、60%/40%、50%/50%、40%/60%、30%/70%。采用三种客观评价指标：PSNR YUV、点云质量度量（PCQM）和GraphSIM。每种编码器均以50%/50%为参考，计算了Bjontegaard Delta。结果表明，增加属性比特率分配通常能带来略优的重建质量。
原文摘要 · Abstract (English)
Typically, point cloud encoders allocate a similar bitrate for geometry and attributes (usually RGB color components) information coding. This paper reports a quality study considering different coding bitrate tradeoff between geometry and attributes. A set of five point clouds, representing different characteristics and types of content was encoded with the MPEG standard Geometry Point Cloud Compression (G-PCC), using octree to encode geometry information, and both the Region Adaptive Hierarchical Transform and the Prediction Lifting transform for attributes. Furthermore, the JPEG Pleno Point Cloud Verification Model was also tested. Five different attributes/geometry bitrate tradeoffs were considered, notably 70%/30%, 60%/40%, 50%/50%, 40%/60%, 30%/70%. Three point cloud objective metrics were selected to assess the quality of the reconstructed point clouds, notably the PSNR YUV, the Point Cloud Quality Metric, and GraphSIM. Furthermore, for each encoder, the Bjonteegaard Deltas were computed for each tradeoff, using the 50%/50% tradeoff as a reference. The reported results indicate that using a higher bitrate allocation for attribute encoding usually yields slightly better results.
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