Set Partitioning in Hierarchical Trees for Point Cloud Attribute Compression

We propose an embedded attribute encoding method for point clouds based on set partitioning in hierarchical trees (SPIHT). The encoder is used with the region-adaptive transform, which has been a popular transform cloud coding and included standard geometry-based coder (G-PCC). result that efficient, scalable, embedded. That is, higher compression achieved by trimming full bit-stream. G-PCC's RAHT coefficient prediction prevents straightforward incorporation of SPIHT into G-PCC. However, our results over other RAHT-based coders are promising, improving original, non-predictive encoder, while providing key functionality being