English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

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

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