Model-based Joint Bit Allocation between Geometry and Color for Video-based 3D Point Cloud Compression
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
---|---|
Pages (from-to) | 3278-3291 |
Number of pages | 14 |
Journal / Publication | IEEE Transactions on Multimedia |
Volume | 23 |
Online published | 10 Sep 2020 |
Publication status | Published - 2021 |
Link(s)
Abstract
In video-based 3D point cloud compression, the quality of the reconstructed 3D point cloud depends on both the geometry and color distortions. Finding an optimal allocation of the total bitrate between the geometry coder and the color coder is a challenging task due to the large number of possible solutions. To solve this bit allocation problem, we first propose analytical distortion and rate models for the geometry and color information. Using these models, we formulate the joint bit allocation problem as a constrained convex optimization problem and solve it with an interior point method. Experimental results show that the rate-distortion performance of the proposed solution is close to that obtained with exhaustive search but at only 0.66% of its time complexity.
Research Area(s)
- Point cloud compression, bit allocation, ratequantization (R-Q) model, distortion-quantization (D-Q) model, rate-distortion optimization (RDO)
Citation Format(s)
Model-based Joint Bit Allocation between Geometry and Color for Video-based 3D Point Cloud Compression. / Liu, Qi; Yuan, Hui; Hou, Junhui et al.
In: IEEE Transactions on Multimedia, Vol. 23, 2021, p. 3278-3291.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review