Adaptive Entropy Coding of Graph Transform Coefficients for Point Cloud Attribute Compression

A point cloud’s attributes constitutes most of its information content. This is why their efficient compression is of great importance when designing a compression scheme. In this paper, the entropy coding stage of an existing compression method is replaced using Context-based Adaptive Binary Arithmetic Coding (CABAC), which is already largely used for video compression applications. Additionally, the DC transform coefficients are quantized with Differential Pulse Code Modulation (DPCM), yielding better performance at lower bit rates. By using predictive coding and coding techniques adapted to the signal’s characteristics, Bjøntegaard Delta rate savings of up to 31.38% are observable in comparison to previously used entropy coding methods.