mlsanityData to 14 Oct 2026

Comments on "Compression of 3D Point Clouds Using a Region-Adaptive Hierarchical Transform"

arXiv 1805.09146 ↗First posted 23 May 2018eess.IVcited by 10

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Abstract (arXiv)

The recently introduced coder based on region-adaptive hierarchical transform (RAHT) for the compression of point clouds attributes, was shown to have a performance competitive with the state-of-the-art, while being much less complex. In the paper "Compression of 3D Point Clouds Using a Region-Adaptive Hierarchical Transform", top performance was achieved using arithmetic coding (AC), while adaptive run-length Golomb-Rice (RLGR) coding was presented as a lower-performance lower-complexity alternative. However, we have found that by reordering the RAHT coefficients we can largely increase the runs of zeros and significantly increase the performance of the RLGR-based RAHT coder. As a result, the new coder, using ordered coefficients, was shown to outperform all other coders, including AC-based RAHT, at an even lower computational cost. We present new results and plots that should enhance those in the work of Queiroz and Chou to include the new results for RLGR-RAHT. We risk to say, based on the results herein, that RLGR-RAHT with sorted coefficients is the new state-of-the-art in point cloud compression.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 May 2018.

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Citing papers per year: 2021: 5; 2022: 4; 2023: 1.

10 papers.