Rate-Distortion Optimized Chroma Quantization for Point Cloud Compression

Point cloud compression is pivotal for the success of immersive multimedia applications. For attribute compression in the geometry-based point cloud compression (G-PCC), Region Adaptive Hierarchical Transform (RAHT) is the preferred coding method. G-PCC performs rate-distortion optimized quantization of luma and chroma residue where they are jointly quantized to zero if deemed to be R-D optimal. However, it is often beneficial to zero out the chroma residue while retaining the luma residue, since chroma exhibits less variations. To address this, we propose rate-distortion (R-D) optimized chroma quantization. Each chroma residue sample is decided to be quantized to zero based on the R-D cost. For accurate R-D cost evaluation, we propose a method to estimate the Lagrange multiplier λ on the fly and further scale it according to the RAHT layers, achieving sequence and layer-wise adaptivity. The method gives 1% effective luma coding gain with negligible increase in complexity. The method has been adopted to the next version of Geometric Solid Test Model (GeS-TM v8.0), a dedicated codec being developed for solid point clouds.