The commit changed to compute UV intra RD estimates for 4x4 and 8x8
separately to be used in mode decision for MB modes associated with
the appropriate transform size respectively. Now finally after many
other changes related 8x8 quantizer zbin boost and zbin_mode_boost,
this change overall helps the HD(with 8x8) by around ~.13%.
(avg .13% glb .13% ssim .17%)
The commit also has a few changes for eliminating compiler warnings.
Change-Id: Ibab35dad44820c87e6b44799c66f8d519cc37344
With this fix, the experimental branch now builds and encodes correctly
with the following two configure options respectively:
--enable-experimental --enable-t8x8
--enable-experimental
Change-Id: I3147c33c503fe713a85fd371e4f1a974805778bf
vp8_fast_quantize_b_pair_neon function added to quantize
two adjacent blocks at the same time to improve performance.
- Additional 3-6% speedup compared to neon optimized fast
quantizer (Tanya VGA@30fps, 1Mbps stream, cpu-used=-5..-16)
Change-Id: I3fcbf141e5d05e9118c38ca37310458afbabaa4e
vp8_fast_quantize_b_neon function updated and further optimized.
- match current C implementation of fast quantizer
- updated to use asm_enc_offsets for structure members
- updated ads2gas scripts to handle alignment issues
Change-Id: I5cbad9c460ad8ddb35d2970a8684cc620711c56d
Changes 'The VP8 project' to 'The WebM project', for consistency
with other webmproject.org repositories.
Fixes issue #97.
Change-Id: I37c13ed5fbdb9d334ceef71c6350e9febed9bbba
Replace the exponential search for optimal rounding during
quantization with a linear Viterbi trellis and enable it
by default when using --best.
Right now this operates on top of the output of the adaptive
zero-bin quantizer in vp8_regular_quantize_b() and gives a small
gain.
It can be tested as a replacement for that quantizer by
enabling the call to vp8_strict_quantize_b(), which uses
normal rounding and no zero bin offset.
Ultimately, the quantizer will have to become a function of lambda
in order to take advantage of activity masking, since there is
limited ability to change the quantization factor itself.
However, currently vp8_strict_quantize_b() plus the trellis
quantizer (which is lambda-dependent) loses to
vp8_regular_quantize_b() alone (which is not) on my test clip.
Patch Set 3:
Fix an issue related to the cost evaluation of successor
states when a coefficient is reduced to zero. With this
issue fixed, now the trellis search almost exactly matches
the exponential search.
Patch Set 2:
Overall, the goal of this patch set is to make "trellis"
search to produce encodings that match the exponential
search version. There are three main differences between
Patch Set 2 and 1:
a. Patch set 1 did not properly account for the scale of
2nd order error, so patch set 2 disable it all together
for 2nd blocks.
b. Patch set 1 was not consistent on when to enable the
the quantization optimization. Patch set 2 restore the
condition to be consistent.
c. Patch set 1 checks quantized level L-1, and L for any
input coefficient was quantized to L. Patch set 2 limits
the candidate coefficient to those that were rounded up
to L. It is worth noting here that a strategy to check
L and L+1 for coefficients that were truncated down to L
might work.
(a and b get trellis quant to basically match the exponential
search on all mid/low rate encodings on cif set, without
a, b, trellis quant can hurt the psnr by 0.2 to .3db at
200kbps for some cif clips)
(c gets trellis quant to match the exponential search
to match at Q0 encoding, without c, trellis quant can be
1.5 to 2db lower for encodings with fixed Q at 0 on most
derf cif clips)
Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
When the license headers were updated, they accidentally contained
trailing whitespace, so unfortunately we have to touch all the files
again.
Change-Id: I236c05fade06589e417179c0444cb39b09e4200d
Added sse2 version of vp8_regular_quantize_b which improved encode
performance(for the clip used) by ~10% for 32 bit builds and ~3% for
64 bit builds.
Also updated SHADOW_ARGS_TO_STACK to allow for more than 9 arguments.
Change-Id: I62f78eabc8040b39f3ffdf21be175811e96b39af
