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Rate-distortion optimized quantization for geometry-based point cloud compression

Tian Guo, Hui Yuan, Lu Wang, Tingting Wang

2023Journal of Electronic Imaging30 citationsDOI

Abstract

Limited by the network bandwidth, three-dimensional (3D) point cloud needs to be efficiently compressed before transmission. As one of the three attribute coding methods adopted in the geometry-based point cloud compression (G-PCC) standard developed by MPEG, predicting transform (PT) has received increasing attention. To further improve the coding efficiency of PT, we propose a rate-distortion optimized quantization (RDOQ) in which an additional option for quantization results is added by setting the quantized residuals to zero forcedly. Rate-distortion optimization is then used to determine whether the final quantized residual should be zero or nonzero. Experimental results show that average BD rates of −0.5 % , −3.0 % , and −3.0 % can be achieved for Luma, Chroma Cb, and Chroma Cr components, respectively, with negligible increment of time complexity.

Topics & Concepts

Quantization (signal processing)Point cloudRate–distortion theoryAlgorithmTransform codingResidualCoding (social sciences)Data compressionRate–distortion optimizationMathematicsComputer scienceRate distortionCloud computingComputer visionDiscrete cosine transformMultiview Video CodingStatisticsVideo processingImage (mathematics)Operating systemVideo trackingComputer Graphics and Visualization Techniques3D Shape Modeling and AnalysisAdvanced Vision and Imaging
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