The first 240 coeff positions (15 top-left blocks) are scanned in the
same order as in scatter scan, after that the coeffs are scanned in
"block bands", each band at a time, all coeffs in one band before
moving on to the next band. This brings down the amount of 4x4 coeff
blocks that need to be buffered while scanning, from 15 blocks to 8 blocks.
Change-Id: I478a991d63c48bd5e64d36e59fed7a00c9a651ba
This patch changes the coefficient tree to move the EOB to below
the ZERO node in order to save number of bool decodes.
The advantages of moving EOB one step down as opposed to two steps down
in the other parallel patch are: 1. The coef modeling based on
the One-node becomes independent of the tree structure above it, and
2. Fewer conext/counter increases are needed.
The drawback is that the potential savings in bool decodes will be
less, but assuming that 0s are much more predominant than 1's the
potential savings is still likely to be substantial.
Results on derf300: -0.237%
Change-Id: Ie784be13dc98291306b338e8228703a4c2ea2242
Proposal for tuning the residual coding by changing how the context
from previous tokens is calculated. Storing the energy class of previous
tokens instead of the token itself eases the critical path of
HW implementations.
Change-Id: I6d71d856b84518f6c88de771ddd818436f794bab
Reverts to using 128 bit LUT for the coef models rather than 48
to ease hardware implementation.
Also incorporates some cleanups including removing various
hooks to support different lookup tables based on block_type and
ref_type.
Change-Id: I54100c120cca07a2ebd3a7776bc4630fa6a153f6
Uses more aggrerssive interpolation to reduce storage for the
model tables by almost more than half. Only 48 lists of probs are
stored (as opposed to 128 before), corresponding to ONE_NODE
probabilities of:
1,
3, 7, 11, ..., 115, 119,
127, 135, ..., 247, 255.
Besides, only 1 table is used as opposed to 2 before. So the overall
memory needed for the tables is just 48 * 8 = 384 bytes.
The table currently used is based on a new Pareto distribution with
heavier tail than a generalized Gaussian - which improves results on
derf by about 0.1% over a single table Generaized Gaussian.
Results overall on derfraw300 is -0.14%.
Change-Id: I19bd03559cbf5894a9f8594b8023dcc3e546f6bd
Cleans up the experiment. Actually uses reduced counts for backward
updates, and reduced number of probabilities in the context.
No change in bitstream when the experiment is on.
Between expt on and off:
derfraw300 is down only -0.062% (which is better than when expts
were run previously).
Change-Id: I55285a049a0c22810bdb42914212ab5a4f8521b5
Change band calculation back to simpler model based
on the order in which coefficients are coded in scan order
not the absolute coefficient positions.
With the scatter scan experiment enabled the results were
appear broadly neutral on derf (-0.028) but up a little on std-hd +0.134).
Without the scatterscan experiment on the results were up derf as well.
Change-Id: Ie9ef03ce42a6b24b849a4bebe950d4a5dffa6791
Turns model based reverse updates on for coefficients in an
effort to reduce the memory requirement for counters.
With this patch the counters needed will be reduced by about
75% since only 3 counts are needed instead of 12.
The impact in performance is:
derf300: -0.252%
stdhd250: -0.046%
However retraining should alleviate some of the drop in
performance.
Change-Id: I6f2b3e13f6d5520aa3400b0b228fb5e8b4a43caa
Adds an experiment that codes an end-of-orientation symbol
for every eligible zero encountered in scan order.
This cleans out various other sub-experiments that were part
of the origiinal patch, which will be later included if found
useful.
Results are slightly positive on all sets (0.1 - 0.2% range).
Change-Id: I57765c605fefc7fb9d1b57f1b356843602abefaf
This patch changes the default with the modecoefprob expt
to use mode-based forward updates with one-node pegged
modeling.
The maximum difference with fully trained tables is now
less that 0.1%.
Change-Id: I06b44322e10c6703f93f3c1d48d973b1136a0618
The patch adds the flexibility to use standard EOB based coding
on smaller block sizes and nzc based coding on larger blocksizes.
The tx-sizes that use nzc based coding and those that use EOB based
coding are controlled by a function get_nzc_used().
By default, this function uses nzc based coding for 16x16 and 32x32
transform blocks, which seem to bridge the performance gap
substantially.
All sets are now lower by 0.5% to 0.7%, as opposed to ~1.8% before.
Change-Id: I06abed3df57b52d241ea1f51b0d571c71e38fd0b
This gains about 0.2% on derf, 0.1% on hd and 0.4% on stdhd. I can put
this under an experimental flag if wanted, just trying to get my patch
queue in shape.
Change-Id: Ibe1a30fe0e0b07bec4802e0f3ff0ba22e505f576
These are mostly just for experimental purposes. I saw small gains (in
the 0.1% range) when playing with this on derf.
Change-Id: Ib21eed477bbb46bddcd73b21c5c708a5b46abedc
Now that the first AC coefficient in both directions use the same DC
as their context, there no longer is a purpose in letting both have
their own band. Merging these two bands allows us to split bands for
some of the very high-frequency AC bands.
In addition, I'm redoing the banding for the 1D-ADST col/row scans. I
don't think the old banding made any sense at all (it merged the last
coefficient of the first row/col in the same band as the first two of
the second row/col), which was clearly an oversight from the band being
applied in scan-order (rather than in their actual position). Now,
coefficients at the same position will be in the same band, regardless
what scan order is used. I think this makes most sense for the purpose
of banding, which is basically "predict energy for this coefficient
depending on the energy of context coefficients" (i.e. pt).
After full re-training, together with previous patch, derf gains about
1.2-1.3%, and hd/stdhd gain about 0.9-1.0%.
Change-Id: I7a0cc12ba724e88b278034113cb4adaaebf87e0c
Pearson correlation for above or left is significantly higher than for
previous-in-scan-order (absolute values depend on position in scan, but
in general, we gain about 0.1-0.2 by using either above or left; using
both basically just makes this even better). For eob branch skipping,
we continue to use the previous token in scan order.
This helps about 0.9% on derf after re-training on a limited data set.
Full re-training and results on larger-resolution clips are pending.
Note that this commit breaks trellis, so we can probably get further
gains out of it by fixing trellis at some later point.
Change-Id: Iead68e296fc3a105cca746b5e3da9555d6010cfe
Replaces the default tables for single coefficient magnitudes with
those obtained from an appropriate distribution. The EOB node
is left unchanged. The model is represeted as a 256-size codebook
where the index corresponds to the probability of the Zero or the
One node. Two variations are implemented corresponding to whether
the Zero node or the One-node is used as the peg. The main advantage
is that the default prob tables will become considerably smaller and
manageable. Besides there is substantially less risk of over-fitting
for a training set.
Various distributions are tried and the one that gives the best
results is the family of Generalized Gaussian distributions with
shape parameter 0.75. The results are within about 0.2% of fully
trained tables for the Zero peg variant, and within 0.1% of the
One peg variant.
The forward updates are optionally (controlled by a macro)
model-based, i.e. restricted to only convey probabilities from the
codebook. Backward updates can also be optionally (controlled by
another macro) model-based, but is turned off by default. Currently
model-based forward updates work about the same as unconstrained
updates, but there is a drop in performance with backward-updates
being model based.
The model based approach also allows the probabilities for the key
frames to be adjusted from the defaults based on the base_qindex of
the frame. Currently the adjustment function is a placeholder that
adjusts the prob of EOB and Zero node from the nominal one at higher
quality (lower qindex) or lower quality (higher qindex) ends of the
range. The rest of the probabilities are then derived based on the
model from the adjusted prob of zero.
Change-Id: Iae050f3cbcc6d8b3f204e8dc395ae47b3b2192c9
The previous implementation visited each node in the tree multiple times
because it used each symbol's encoding to revisit the branches taken and
increment its count. Instead, we can traverse the tree depth first and
calculate the probabilities and branch counts as we walk back up. The
complexity goes from somewhere between O(nlogn) and O(n^2) (depending on
how balanced the tree is) to O(n).
Only tested one clip (256kbps, CIF), saw 13% decoding perf improvement.
Note that this optimization should port trivially to VP8 as well. In VP8,
the decoder doesn't use this function, but it does routinely show up
on the profile for realtime encoding.
Change-Id: I4f2848e4f41dc9a7694f73f3e75034bce08d1b12
Adds probability updates for extra bits for the nzcs, code for
getting nzc stats, plus some minor cleanups and fixes.
Change-Id: If2814e7f04fb52f5025ad9f400f3e6c50a00b543
This patch revamps the entropy coding of coefficients to code first
a non-zero count per coded block and correspondingly remove the EOB
token from the token set.
STATUS:
Main encode/decode code achieving encode/decode sync - done.
Forward and backward probability updates to the nzcs - done.
Rd costing updates for nzcs - done.
Note: The dynamic progrmaming apporach used in trellis quantization
is not exactly compatible with nzcs. A suboptimal approach has been
used instead where branch costs are updated to account for changes
in the nzcs.
TODO:
Training the default probs/counts for nzcs
Change-Id: I951bc1e22f47885077a7453a09b0493daa77883d
Split macroblock and superblock tokenization and detokenization
functions and coefficient-related data structs so that the bitstream
layout and related code of superblock coefficients looks less like it's
a hack to fit macroblocks in superblocks.
In addition, unify chroma transform size selection from luma transform
size (i.e. always use the same size, as long as it fits the predictor);
in practice, this means 32x32 and 64x64 superblocks using the 16x16 luma
transform will now use the 16x16 (instead of the 8x8) chroma transform,
and 64x64 superblocks using the 32x32 luma transform will now use the
32x32 (instead of the 16x16) chroma transform.
Lastly, add a trellis optimize function for 32x32 transform blocks.
HD gains about 0.3%, STDHD about 0.15% and derf about 0.1%. There's
a few negative points here and there that I might want to analyze
a little closer.
Change-Id: Ibad7c3ddfe1acfc52771dfc27c03e9783e054430
This patch alters the balance of context between the
coefficient bands (reflecting the position of coefficients
within a transform blocks) and the energy of the previous
token (or tokens) within a block.
In this case the number of coefficient bands is reduced
but more previous token energy bands are supported.
Some initial rebalancing of the default tables has been
by running multiple derf clips at multiple data rates using
the ENTOPY_STATS macro. Further balancing needs to be
done using larger image formatsd especially in regard to
the bigger transform sizes which are not as well represented
in encodings of smaller image formats.
Change-Id: If9736e95c391e711b04aef6393d26f60f36e1f8a
This patch abstracts the selection of the coefficient band
context into a function as a precursor to further experiments
with the coefficient context.
It also removes the large per TX size coefficient band structures
and uses a single matrix for all block sizes within the test function.
This may have an impact on quality (results to follow) but is only an
intermediate step in the process of redefining the context. Also the
quality impact will be larger initially because the default tables will
be out of step with the new banding.
In particular the 4x4 will in this case only use 7 bands. If needed we
can add back block size dependency localized within the function, but
this can follow on after the other changes to the definition of the
context.
Change-Id: Id7009c2f4f9bb1d02b861af85fd8223d4285bde5
This is an initial step to facilitate experimentation
with changes to the prior token context used to code
coefficients to take better account of the energy of
preceding tokens.
This patch merely abstracts the selection of context into
two functions and does not alter the output.
Change-Id: I117fff0b49c61da83aed641e36620442f86def86
Removal of the NEWCOEFCONTEXT experiment to
reduce code clutter and make it easier to experiment with
some other changes to the coefficient coding context.
Change-Id: Icd17b421384c354df6117cc714747647c5eb7e98
Fixes some scaling issues. Adds an option to only compute the
dct on the low-low subband for 32x32 and 64x64 blocks using
only a single 16x16 dct after 1 and 2 wavelet decomposition
levels respectively. Also adds an option to use a 8x8 dct
as building block.
Currenlty with the 2/6 filter and with a single 16x16 dct on
the low low band, the reuslts compared to full 32x32 dct is
as follows:
derf: -0.15%
yt: -0.29%
std-hd: -0.18%
hd: -0.6%
These are my current recommended settings, since the 2/6 filter
is very simple.
Results with 8x8 dct are about 0.3% worse.
Change-Id: I00100cdc96e32deced591985785ef0d06f325e44
This is to add to the 64x64 transform experiment as an alternative to
a 64x64 DCT.
Two levels of wavelet decomposition is used on a 64x64 block, followed
by 16x16 DCT on the four lowest subbands. The highest three subbands
are left untransformed after the first level DWT.
Change-Id: I3d48d5800468d655191933894df6b46e15adca56
