.png){kind=icon}
.png){kind=icon}
Return
Block size selection in rate-constrained geometry based point cloud compression
.png){kind=icon}
PRE
AI
DOI：10.1007/s11042-021-11672-8.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In geometry-based point cloud compression, the geometry information is typically compressed using octree coding. In octree coding, the size of the blocks in the voxelized point clouds, i.e., the number of voxels contained in a block, determines whether the geometry coding is lossless or lossy, and the degree of geometry compression in lossy coding. Therefore, selecting an appropriate block size for octree coding is crucial for compression quality of voxelized point clouds. In this paper, we propose an optimal block size selection scheme for geometry based point cloud compression with a given bit rate constraint. Firstly, we analyze the gradients of the overall quality of the point clouds with color coding bit rate and geometry coding bit rate in lossy geometry coding. Then, we propose an octree level selection approach that can output the optimal octree level for point cloud compression under a target bit rate. In this approach, we consider the difference between the impacts of lossy geometry coding and lossless geometry coding on the overall quality of the point clouds. Experimental results demonstrate that, using the level selected by the proposed algorithm for geometry coding can yield best coding results in terms of the average quality of the images rendered from decoded point clouds.
Keywords:
Block size selection
Rate constrained
Octree level
Point cloud compression
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3
Papers:
1.9W
Citations:
3.2W
Organization
No organization information available