Model-based Joint Bit Allocation between Geometry and Color for Video-based 3D Point Cloud Compression

Qi Liu, Hui Yuan*, Junhui Hou, Raouf Hamzaoui, Honglei Su

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

57 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)3278-3291
Number of pages14
JournalIEEE Transactions on Multimedia
Volume23
Online published10 Sept 2020
DOIs
Publication statusPublished - 2021

Research Keywords

  • Point cloud compression
  • bit allocation
  • ratequantization (R-Q) model
  • distortion-quantization (D-Q) model
  • rate-distortion optimization (RDO)

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