this avoids duplicates between these trees and dsp/, e.g., enc/tree.c,
dec/tree.c, making pulling the whole library source tree into one target
possible
BUG=webp:279
Change-Id: I060a614833c7c24ddd37bf641702ae6a5eef1775
For some reason, gcc has hard time inlining this one...
Also optimize predictor #0 and #1 for encoding, so we don't have to
call the generic pointers VP8LPredictors[...]
Change-Id: I1ff31e3b83874b53f84fe23487f644619fd61db9
Having it architecture dependent resulted in an extra
function call of an extern function, hence no inlining and
a 5-10% impact on performance.
Change-Id: I0ff40d2d881edc76d3594213a64ee53097d42450
We add the following MSA optimized color transform functions:
- TransformColor
- SubtractGreenFromBlueAndRed
Change-Id: Ib182d2b5faa7191f503ce70f0dfde0ac89402fd3
The old implementation in enc/near_lossless.c performing a separate
preprocessing step is used only when a prediction filter is not used,
otherwise a new implementation integrated into lossless_enc.c is used.
It retains the same logic for converting near lossless quality into max
number of bits dropped, and for adjusting the number of bits based on
the smoothness of the image at a given pixel. As before, borders are not
changed.
Then, instead of quantizing raw component values, the residual after
subtract green and after prediction is quantized according to the
resulting number of bits, taking care to not cross the boundary between
255 and 0 after decoding. Ties are resolved by moving closer to the
prediction instead of by bankers’ rounding.
This results in about 15% size decrease for the same quality.
Change-Id: If3e9c388158c2e3e75ef88876703f40b932f671f
The code and logic is unified when computing bit entropy + Huffman cost.
Speed-wise, we gain 8% for lossless encoding.
Logic-wise, the beginning/end of the distributions are handled properly
and the compression ratio does not change much.
Change-Id: Ifa91d7d3e667c9a9a421faec4e845ecb6479a633
The functions containing magic constants are moved out of ./dsp .
VP8LPopulationCost got put back in ./enc
VP8LGetCombinedEntropy is now unrefined (refinement happening in ./enc)
VP8LBitsEntropy is now unrefined (refinement happening in ./enc)
VP8LHistogramEstimateBits got put back in ./enc
VP8LHistogramEstimateBitsBulk got deleted.
Change-Id: I09c4101eebbc6f174403157026fe4a23a5316beb
CombinedShannonEntropy takes 30% for lossless compression.
This implementation speeds up the overall process by 2 to 3 %.
Change-Id: I04a71743284c38814fd0726034d51a02b1b6ba8f
Gives 0.9% smaller (2.4% compared to before alpha cleanup) size on the 1000 PNGs dataset:
Alpha cleanup before: 18856614
Alpha cleanup after: 18685802
For reference, with no alpha cleanup: 19159992
Note: WebPCleanupTransparentArea is still also called in WebPEncode. This cleanup still helps
preprocessing in the encoder, and the cases when the prediction transform is not used.
Change-Id: I63e69f48af6ddeb9804e2e603c59dde2718c6c28
for more speed.
This gives a roughly a 1% speedup for low_effort. But actually this is a
preparation for the upcoming CL that changes RGB values of transparent pixels
based on prediction, which should not be done for low_effort because that would
slightly hurt its performance.
On 1000 PNGs, with quality 0, method 0:
Before:
Compression (output/input): 2.9120/3.2667 bpp, Encode rate (raw data): 36.034 MP/s
After:
Compression (output/input): 2.9120/3.2667 bpp, Encode rate (raw data): 36.428 MP/s
Change-Id: I5ed9f599bbf908a917723f3c780551ceb7fd724d
The same computation was done for both values: go over two buffers,
sum them up, and take a decision on the sum at each iteration.
MIPS32 code has been disabled for now, pending a code update.
Change-Id: I997984326f7092b3dbb8cfa1e524bd8132b2ab9d
instead of per block. This prepares for a next CL that can make the
predictors alter RGB value behind transparent pixels for denser
encoding. Some predictors depend on the top-right pixel, and it must
have been already processed to know its new RGB value, so requires per
scanline instead of per block.
Running the encode speed test on 1000 PNGs 10 times with default
settings:
Before:
Compression (output/input): 2.3745/3.2667 bpp, Encode rate (raw data): 1.497 MP/s
After:
Compression (output/input): 2.3745/3.2667 bpp, Encode rate (raw data): 1.501 MP/s
Same but with quality 0, method 0 and 30 iterations:
Before:
Compression (output/input): 2.9120/3.2667 bpp, Encode rate (raw data): 36.379 MP/s
After:
Compression (output/input): 2.9120/3.2667 bpp, Encode rate (raw data): 36.462 MP/s
No effect on compressed size, this produces exactly same files. No
significant measured effect on speed. Expected faster speed from better
memory layout with scanline processing but slower speed due to needing
to get predictor mode per pixel, may compensate each other.
Change-Id: I40f766f1c1c19f87b62c1e2a1c4cd7627a2c3334
share the computation between different modes
3-5 % speedup for lossless alpha
1 % for lossy alpha
no change in compression density
Change-Id: I5e31413b3efcd4319121587da8320ac4f14550b2
New implementations: SubtractGreenFromBlueAndRed and TransformColor
around 1-2% faster lossless encoding.
Change-Id: I1668e36fdc316ba55b3b798b91b4a3e36ce62861
over a 1000 image corpus
Single photograph benchmark:
Before:
Q=20: 2.560 MP/s
Q=40: 2.593 MP/s
Q=60: 1.795 MP/s
Q=80: 1.603 MP/s
Q=99: 1.122 MP/s
After:
Q=20: 3.334 MP/s
Q=40: 2.464 MP/s
Q=60: 2.009 MP/s
Q=80: 1.871 MP/s
Q=99: 1.163 MP/s
This CL allows for some further improvements that would not be possible
otherwise.
Change-Id: I61ba154beca2266cb96469281cf96e84a4412586
