Tzamarias Dion E O, Chow Kevin, Blanes Ian, Serra-Sagrista Joan
IEEE Trans Image Process. 2022;31:4490-4501. doi: 10.1109/TIP.2022.3185541. Epub 2022 Jul 1.
The increase in popularity of point-cloud-oriented applications has triggered the development of specialized compression algorithms. In this paper, a novel algorithm is developed for the lossless geometry compression of voxelized point clouds following an intra-frame design. The encoded voxels are arranged into runs and are encoded through a single-pass application directly on the voxel domain. This is done without representing the point cloud via an octree nor rendering the voxel space through an occupancy matrix, therefore decreasing the memory requirements of the method. Each run is compressed using a context-adaptive arithmetic encoder yielding state-of-the-art compression results, with gains of up to 15% over TMC13, MPEG's standard for point cloud geometry compression. Several proposed contributions accelerate the calculations of each run's probability limits prior to arithmetic encoding. As a result, the encoder attains a low computational complexity described by a linear relation to the number of occupied voxels leading to an average speedup of 1.8 over TMC13 in encoding speeds. Various experiments are conducted assessing the proposed algorithm's state-of-the-art performance in terms of compression ratio and encoding speeds.
面向点云的应用程序的日益普及引发了专门压缩算法的发展。在本文中，我们开发了一种新颖的算法，用于按照帧内设计对体素化点云进行无损几何压缩。编码后的体素被排列成游程，并通过直接在体素域上的单遍应用进行编码。这一过程无需通过八叉树表示点云，也无需通过占用矩阵渲染体素空间，因此降低了该方法的内存需求。每个游程使用上下文自适应算术编码器进行压缩，从而产生了领先的压缩结果，与MPEG的点云几何压缩标准TMC13相比，增益高达15%。本文提出的几个改进措施加速了算术编码之前每个游程概率极限的计算。结果，编码器实现了较低的计算复杂度，其与占用体素数量呈线性关系，在编码速度方面比TMC13平均加速了1.8倍。我们进行了各种实验，从压缩率和编码速度方面评估了所提出算法的领先性能。
