  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.
