Internet DRAFT - draft-midtskogen-netvc-clpf
draft-midtskogen-netvc-clpf
Network Working Group S. Midtskogen
Internet-Draft A. Fuldseth
Intended status: Standards Track M. Zanaty
Expires: September 11, 2017 Cisco
March 10, 2017
Constrained Low Pass Filter
draft-midtskogen-netvc-clpf-04
Abstract
This document describes a low complexity filtering technique which is
being used as a low pass loop filter in the Thor video codec.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Definitions . . . . . . . . . . . . . . . . . . . . . . . . . 2
2.1. Requirements Language . . . . . . . . . . . . . . . . . . 2
2.2. Terminology . . . . . . . . . . . . . . . . . . . . . . . 2
3. Filtering Process . . . . . . . . . . . . . . . . . . . . . . 3
4. Further complexity considerations . . . . . . . . . . . . . . 6
5. Performance . . . . . . . . . . . . . . . . . . . . . . . . . 6
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 7
7. Security Considerations . . . . . . . . . . . . . . . . . . . 7
8. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 7
9. References . . . . . . . . . . . . . . . . . . . . . . . . . 8
9.1. Normative References . . . . . . . . . . . . . . . . . . 8
9.2. Informative References . . . . . . . . . . . . . . . . . 8
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 8
1. Introduction
Modern video coding standards such as Thor [I-D.fuldseth-netvc-thor]
include in-loop filters which correct artifacts introduced in the
encoding process. Thor includes a deblocking filter which corrects
artifacts introduced by the block based nature of the encoding
process, and a low pass filter correcting artifacts not corrected by
the deblocking filter, in particular artifacts introduced by
quantisation errors of transform coefficients and by the
interpolation filter. Since in-loop filters have to be applied in
both the encoder and decoder, it is highly desirable that these
filters have low computational complexity.
2. Definitions
2.1. Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119].
2.2. Terminology
This document will refer to a pixel X and eight of its neighbouring
pixels A - H ordered in the following pattern.
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+---+---+---+---+---+
| | | A | | |
+---+---+---+---+---+
| | | B | | |
+---+---+---+---+---+
| C | D | X | E | F |
+---+---+---+---+---+
| | | G | | |
+---+---+---+---+---+
| | | H | | |
+---+---+---+---+---+
Figure 1: Filter pixel positions
In Thor the frames are divided into filter blocks (FB) of 128x128,
64x64 or 32x32 pixels, which is signalled for each frame to be
filtered. Also, each frame is divided into coding blocks (CB) which
range from 8x8 to 128x128 independent of the FB size. The filter
described in this draft can be switched on or off for the entire
frame or optionally on or off for each FB. CB's that have been coded
using the skip mode are not filtered, and if a FB only contains CB's
that have been coded in skip mode, the FB will not be filtered and no
signal will be transmitted for this FB.
If the frame can't fit a whole number of FB's, the FB's at the right
and bottom edges are clipped to fit. For instance, if the frame
resolution is 1920x1080 and the FB size is 128x128, the size of the
FB's at the bottom of the frame becomes 128x56.
3. Filtering Process
Given a pixel X and its neighbouring pixels described above we can
define a general non-linear filter as:
X' = X + a*constrain(A-X) + b*constrain(B-X) +
c*constrain(C-X) + d*constrain(D-X) +
e*constrain(E-X) + f*constrain(F-X) +
g*constrain(G-X) + h*constrain(H-X)
Figure 2: Equation 1
where constrain(x) is a function limiting the range of x.
If a neighbour pixel is outside the image frame, it is given the same
value as the closest pixel within the frame. To avoid dependencies
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prohibiting parallel processing, all neighbour pixels must be the
unfiltered pixels of the frame being filtered.
Experiments in Thor have shown that a good compromise between
complexity and performance is a=c=f=h=1/16, b=d=e=g=3/16, and a good
constrain function has been found to be:
constrain(x, s, d) =
sign(x) * max(0, abs(x) - max(0, abs(x) - s +
(abs(x) >> (d - log2(s)))))
Figure 3: Equation 2
where sign(x) returns 1 or -1 if x is positive or negative
respectively, s denotes the strength of the filter by which x will be
clipped, and d further constrains the range of x so that the output
of the function will linearly approach 0 as abs(x) approaches 2^d. d
depends on the frame quality (qp) and is computed as
d = bitdepth - 4 + qp/16
Figure 4: Equation 4
for the luma plane and
d = bitdepth - 5 + qp/16
Figure 5: Equation 5
for the chroma planes.
The constrain function can be visualised as follows
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s ----
/ ----
/ ----
0 ------------ / ------------
---- /
---- /
s ----
-2^d -s 0 s 2^d
Figure 6: Graph 1
The filter strength s can be 1, 2 or 4 signalled at frame level when
the bitdepth is 8. The strengths are scaled according to the
bitdepth, so they become 4, 8 and 16 when the bitdepth is 10, and 16,
32 and 64 when the bitdepth is 12. The rounding is to the nearest
integer.
This gives us the equation:
X' = X + (1*constrain(A-X, s, d) + 3*constrain(B-X, s, d) +
(1*constrain(C-X, s, d) + 3*constrain(D-X, s, d) +
(3*constrain(E-X, s, d) + 1*constrain(F-X, s, d) +
(3*constrain(G-X, s, d) + 1*constrain(H-X, s, d)
Figure 7: Equation 6
The filter leaves the encoder 13 different choices for a frame. The
filter can be disabled for the entire frame, or the frame is filtered
using all distinct combinations of strength (1, 2 or 4 scaled for
bitdepth), non-skip FB signal (enabled/disabled) and FB size (32x32,
64x64 or 128x128). Note that the FB size only matters when FB
signalling is in use.
The decisions at both frame level and FB level may be based on rate-
distortion optimisation (RDO), but an encoder running in a low-
complexity mode, or possibly a low-delay mode, may instead assume
that a fixed mode will be beneficial. In general, using s=2, a QP
dependent FB size and RDO only at the FB level gives good results.
However, because of the low complexity of the filter, fully RDO based
decisions are not costly. The distortion of the 13 configurations of
the filter can easily be computed in a single pass by keeping track
of the distortions of the three different strengths and the bit costs
for different FB sizes.
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The filter is applied after the deblocking filter.
4. Further complexity considerations
The filter has been designed to offer the best compromise between low
complexity and performance. All operations are easily vectorised
with SIMD instructions and if the video input is 8 bit, all SIMD
operations can have 8 bit lanes in architectures such as x86/SSE4 and
ARM/NEON. Clipping at frame borders can be implemented using shuffle
instructions.
5. Performance
The table below shows filters effect on the bandwidth for a selection
of 10 second video sequences encoded in Thor with uni-prediction
only. The numbers have been computed using the Bjontegaard Delta
Rate (BDR). BDR-low and BDR-high indicate the effect at low and high
bitrates, respectively, as described in BDR [BDR].
The effect of the filter was tested in two encoder low-delay
configurations: high complexity in which the encoder strongly favours
compression efficiency over CPU usage, and medium complexity which is
more suited for real-time applications. The bandwidth reduction is
somewhat less in the high complexity configuration.
+----------------+--------------------+--------------------+
| | MEDIUM COMPLEXITY | HIGH COMPLEXITY |
+----------------+------+------+------+--------------------+
| | | BDR- | BDR- | | BDR- | BDR- |
|Sequence | BDR | low | high | BDR | low | high |
+----------------+------+------+------+------+------+------+
|Kimono | -2.6%| -2.3%| -3.2%| -1.7%| -1.7%| -1.9%|
|BasketballDrive | -3.9%| -3.1%| -5.0%| -2.8%| -2.4%| -3.5%|
|BQTerrace | -7.4%| -4.0%|-10.2%| -4.8%| -2.4%| -6.8%|
|FourPeople | -5.5%| -3.9%| -8.2%| -3.8%| -2.9%| -5.1%|
|Johnny | -5.2%| -3.5%| -8.2%| -3.3%| -2.7%| -4.5%|
|ChangeSeats | -6.4%| -3.9%|-10.2%| -4.7%| -2.6%| -6.9%|
|HeadAndShoulder | -9.3%| -3.4%|-19.6%| -6.2%| -2.6%|-11.8%|
|TelePresence | -5.8%| -3.6%|-10.0%| -4.5%| -3.3%| -6.6%|
+----------------+------+------+------+--------------------+
|Average | -5.8%| -3.5%| -9.3%| -4.0%| -2.6%| -5.9%|
+----------------+------+------+------+--------------------+
Figure 8: Compression Performance without Biprediction
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While the filter objectively performs better at relatively high
bitrates, the subjective effect seems better at relatively low
bitrates, and overall the subjective effect seems better than what
the objective numbers suggest.
If biprediction is allowed, there is generally less bandwidth
reduction as the table below shows. These results reflect low-delay
biprediction without frame reordering.
+----------------+--------------------+--------------------+
| | MEDIUM COMPLEXITY | HIGH COMPLEXITY |
+----------------+------+------+------+--------------------+
| | | BDR- | BDR- | | BDR- | BDR- |
|Sequence | BDR | low | high | BDR | low | high |
+----------------+------+------+------+------+------+------+
|Kimono | -2.2%| -2.0%| -2.7%| -1.4%| -1.3%| -1.5%|
|BasketballDrive | -3.1%| -3.0%| -3.3%| -1.9%| -2.0%| -1.7%|
|BQTerrace | -5.4%| -4.3%| -6.5%| -3.9%| -3.6%| -3.8%|
|FourPeople | -3.8%| -2.8%| -5.2%| -2.4%| -1.8%| -3.0%|
|Johnny | -3.8%| -3.1%| -4.8%| -2.4%| -2.2%| -2.7%|
|ChangeSeats | -4.4%| -3.1%| -6.5%| -3.2%| -2.6%| -3.9%|
|HeadAndShoulder | -4.8%| -3.0%| -8.1%| -3.0%| -2.7%| -3.7%|
|TelePresence | -3.4%| -2.3%| -5.5%| -2.2%| -1.7%| -3.1%|
+----------------+------+------+------+------+------+------+
|Average | -3.9%| -2.9%| -5.3%| -2.5%| -2.2%| -2.9%|
+----------------+------+------+------+------+------+------+
Figure 9: Compression Performance with Biprediction
6. IANA Considerations
This document has no IANA considerations yet. TBD
7. Security Considerations
This document has no security considerations yet. TBD
8. Acknowledgements
The authors would like to thank Gisle Bjontegaard for reviewing this
document and design, and providing constructive feedback and
direction.
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9. References
9.1. Normative References
[I-D.fuldseth-netvc-thor]
Fuldseth, A., Bjontegaard, G., Midtskogen, S., Davies, T.,
and M. Zanaty, "Thor Video Codec", draft-fuldseth-netvc-
thor-03 (work in progress), October 2016.
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<http://www.rfc-editor.org/info/rfc2119>.
9.2. Informative References
[BDR] Bjontegaard, G., "Calculation of average PSNR differences
between RD-curves", ITU-T SG16 Q6 VCEG-M33 , April 2001.
Authors' Addresses
Steinar Midtskogen
Cisco
Lysaker
Norway
Email: stemidts@cisco.com
Arild Fuldseth
Cisco
Lysaker
Norway
Email: arilfuld@cisco.com
Mo Zanaty
Cisco
RTP,NC
USA
Email: mzanaty@cisco.com
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