Progressive encoding of binary voxel models using pyramidal decomposition
In this paper, we propose a progressive encoding algorithm for the geometric information of a 3D object, which is represented by binary voxels. Using the morphological pyramidal decomposition, the proposed algorithm first generates the multi-resolution models of a 3D object. Then, each resolution model is predicted from its lower resolution model, and the prediction errors are encoded using an arithmetic coding technique. To yield high compression ratio, each model is partitioned into the inside, boundary, and outside regions based on the lower resolution model. This partitioning method greatly reduces the amount of data to be encoded, since the prediction errors are compactly concentrated near the boundary region. Moreover, the neighborhood relation of each boundary voxel is used as the context for the arithmetic coding to further increase the compression efficiency. It is demonstrated by extensive simulation results that the proposed algorithm provides better coding gain than the conventional voxel and mesh compression algorithms.
progressive encoding binary voxels