Khaled Mammou authored Jun 30, 2018 and David Flynn committed Aug 20, 2018

Adaptively pick the number of neighbours considered during the
prediction based on analysis of the reconstructed attribute values of
the neighbours.

From m42642, this is performed by computing the maximum difference
between any two reconstructed attribute values of a points neighbours.
If the variability is higher than a threshold, then apply a
rate-distortion optimization procedure to choose between using either
a single neighbour or all neighbours. The index of the best prediction
strategy is arithmetically encoded.

This commit:
 - implements the m42642 method
 - moves buildPredictors into transform-specific attribute encoding/decoding
 - adds quantizationStepsChroma
 - renames quantizationSteps -> quantizationStepsLuma

df: fixed incorrect application of quantizationStepsLuma|Chroma
df: updated cat3 cfg to specify quantizationStepsChroma
df: fixed header encoding if quantizationStepsChroma missing