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Intra-Frame Compression of Point Cloud Geometry Using Dyadic Decomposition

Eduardo Peixoto

2020IEEE Signal Processing Letters32 citationsDOI

Abstract

This letter presents a lossless intra coder of the geometry information of voxelized point clouds. Instead of using the popular octree decomposition, the proposed method views the point cloud geometry as an array of bi-level images, and it is inspired by well-known techniques for coding this type of images. This array is encoded using a dyadic decomposition that recursively splits the array into two arrays of half its size, transmitting the occupancy information of each smaller array. Context adaptive arithmetic coding, using both 2D and 3D contexts, is used to achieve efficient compression. Results show that the proposed method outperforms all state-of-the-art intra coders on the public available point cloud datasets tested.

Topics & Concepts

Lossless compressionPoint cloudOctreeArithmetic codingComputer scienceCoding (social sciences)Data compressionCompression (physics)AlgorithmPoint (geometry)Context (archaeology)GeometryMathematicsComputer visionContext-adaptive binary arithmetic codingPaleontologyStatisticsBiologyMaterials scienceComposite material3D Shape Modeling and AnalysisComputer Graphics and Visualization TechniquesRemote Sensing and LiDAR Applications
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