Early Termination of Dyadic Region-Adaptive Hierarchical Transform for Efficient Attribute Compression of 3D Point Clouds

Hooda, Reetu; Pan, W. David

doi:10.1109/lsp.2021.3133204

Cited by 6 publications

(1 citation statement)

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“…Xu et al 26 represented dynamic point clouds on spatial-temporal graphs and modeled them with Gaussian Markov random fields concerning the underlying graphs, from which they derived optimal interprediction and predictive transforms for attribute compression of dynamic point clouds. Based on RAHT, 27 Hooda and Pan 28 proposed an adaptive scheme of switching between RAHT and Dyadic RAHT to achieve early termination of Dyadic RAHT by using 3D gradient filters. To achieve better RD performance for PT, Zhang et al 29 added a modification parameter intraPredictionWeight to set the optimal weights of neighboring points.…”

Section: Related Workmentioning

confidence: 99%

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

et al. 2023

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.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.

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Section: Related Workmentioning

confidence: 99%