Merge pull request #49775 from fire/faster-cvtt

Faster CVTT by lowering default quality

1 files changed, 27 insertions, 0 deletions

diff --git a/thirdparty/cvtt/etc_notes.txt b/thirdparty/cvtt/etc_notes.txt
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+The ETC1 compressor uses modified cluster fit:
+
+Assume that there exists an ideal base color and set of selectors for a given table.
+For a given table and set of selectors, the ideal base color can be determined by subtracting the offsets from each pixel and averaging them.
+Doing that is equivalent to subtracting the average offset from the average color.
+Because positive and negative selectors of the same magnitude cancel out, the search space of possible average offsets is reduced: 57 unique offsets for the first table and 81 for the others.
+Most of the offsets result in the same color as another average offset due to quantization of the base color, so those can be de-duplicated.
+So:
+- Start with a high-precision average color.
+- Apply precomputed luma offsets to it.
+- Quantize and de-duplicate the base colors.
+- Find the ideal selectors for each base color.
+
+Differential mode is solved by just finding the best legal combination from those attempts.
+
+There are several scenarios where this is not ideal:
+- Clamping behavior can sometimes be leveraged for a more accurate block.
+- Differentials can sometimes be moved slightly closer to become legal.
+- This only works when MSE is the error metric (i.e. not normal maps)
+- This only works when pixel weights are of equal importance (i.e. not using weight by alpha or edge deblocking)
+
+T and H mode just work by generating clustering assignments by computing a chrominance line and splitting the block in half by the chrominance midpoint and using those to determine the averages.
+
+Planar mode is just solved algebraically.
+
+If you want to emulate etc2comp's default settings, add the flag ETC_UseFakeBT709 to use its modified Rec. 709 error coefficients.
+Doing that will significantly slow down encoding because it requires much more complicated quantization math.
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