Lossy Point Cloud Geometry Compression Via Dyadic Decomposition

This paper proposes a lossy intra-frame coder of the geometry information of voxelized point clouds. Using an alternative approach to the widespread octree representation, this method represents the point cloud as an array of binary images. This algorithm works recursively using a dyadic decomposition that splits an interval of slices in two smaller intervals, depicting a binary tree traversal, and transmitting the occupancy information of each interval. The sequence of bi-level images are encoded in a lossless fashion until a fixed point in the tree, from where the algorithm “skips” the dyadic slicing and transmits all the k remaining slices as leaves of the tree, which are then encoded in a lossy fashion. The performance assessment shows that the proposed method outperforms state-of-the-art intra coders of lossy geometry for medium to higher bitrates on the public point cloud datasets tested.