Intra-Frame Compression of Point Cloud Geometry Using Dyadic Decomposition

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...

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Bibliographic Details
Published in:IEEE signal processing letters 2020, Vol.27, p.246-250
Main Author: Peixoto, Eduardo
Format: Article
Language:English
Subjects:
Arithmetic coding
Arrays
Coders
Decomposition
Encoding
Geometry
Image coding
intra coder
lossless coding
Occupancy
Octrees
Point clouds
Signal processing algorithms
Three-dimensional displays
Two dimensional displays
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Description
Summary: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.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2020.2965322