HARSHA NAGATHIHALLI JAGADISH 1001296212 Acronyms AVC Advanced Video Coding BS Boundary Strength CODEC COder DECoder Croma Chrominance CTU Coding Tree Unit CU Coding Unit DCT Discrete Cosine Transform ID: 551522
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Slide1
SAMPLE ADAPTIVE OFFSET IN THE HEVC STANDARD
HARSHA NAGATHIHALLI JAGADISH (1001296212)Slide2
Acronyms
AVC: Advanced Video Coding
BS: Boundary Strength
CODEC:
COder
/
DECoder
Croma
: Chrominance
CTU: Coding Tree Unit
CU: Coding Unit
DCT: Discrete Cosine Transform
DFT: Discrete Fourier Transform
HEVC: High Efficiency Video Coding
ITU-T: International Telecommunication Union (Telecommunication Standardization Sector)
IEC: International
Electrotechnical
Commission
ISO: International Standards Organization
JBIG: Joint Bi-level Image Experts Group
JPEG: Joint photographic experts groupSlide3
JCT-VC: Joint collaborative team on video coding
LOT: Lapped Orthogonal Transform
Luma
: Luminance
MB: Macro Block
MPEG: Moving picture experts group
OBMC: Overlapped Block Motion Compensation
PU: Prediction Unit
QP: Quantization Parameter
SAO: Sample Adaptive Offset
TU: Transform UnitSlide4
Introduction
The HEVC standard specifies two in-loop filters, a
deblocking
filter
and a
sample adaptive offset (SAO
).
Since the deblocking
and SAO
attenuate different artifacts, their benefits are additive when used
together.
SAO is a process that modifies the decoded samples by conditionally adding an offset value to each sample after the application of the
deblocking
filter, based on values in look-up tables transmitted by the encoder.Slide5
Motivation
A larger
transform could introduce more artifacts
including ringing
artifacts that mainly come from quantization errors
of transform coefficients[2]
A higher number of
interpolation taps can
also lead to more serious ringing artifacts. Hence, it
is necessary
to
incorporate SAO technique in HEVC.
SAO not only is useful in HEVC but
also can
be applied on top of AVC and other prior video
coding standards
.Slide6
Evolution
In Windows
Media Video
9 [3]
deringing
filter was applied for reducing ringing artifacts
samples are classified into two categories: edge and
nonedge
WMV9 is a post-processing technique, which might lead to serious flickering artifacts from picture to picture.
The features of the SAO in JCTVC-E049 [4]
Step 1 :it
allows local adaptation
Step 2 :
sequential stages are combined into
one stage
by selecting only one classifier per region to reduce
the encoding
latency.
Step 3:
2-D edge classification patterns
are removed
, and only four 1-D edge classification patterns
are used.
Step 4: Fast distortion
estimation Slide7
Brief Overview
Sample Adaptive Offset (
SAO)Filter
Calculates
edge and band
offsets signaled
to decoder
Offsets
added to reconstructed pixels
SAO is not restricted to
block boundaries
[2]Slide8
HEVC Encoder
Fig.2 HEVC Encoder Diagram
In-loop filters
[
1
]Slide9
Sample Processing
Two SAO types that
can satisfy
the requirements of low complexity are adopted
in HEVC
:
Edge offset (EO) and
Band offset (BO).
For
EO , the
sample classification is based on comparison
between current
samples and neighboring samples.For BO, the sample classification is based on sample
values.To reduce side information, multiple CTUs can be merged together to share
SAO
parameters.Slide10
a)Edge offset mode
In
the
edge offset
mode,
EO
uses four 1-D directional patterns
for sample
classification
:
horizontal
, vertical, 135° diagonal,
and 45°
diagonal as shown in fig.3
[5]
3Slide11
Contd..
For a given EO class, each sample inside the CTB
is classified
into one of five categories
The current sample
value, labeled
as “c,” is compared with its two neighbors along
the selected
1-D pattern
.
Categories 1 and 4 are
associated with
a
local valley and a local peak along the selected
1-D pattern
, respectively
.
Categories 2 and 3 are associated
with
concave
and convex corners along the selected 1-D
pattern, respectively
.Slide12
Contd..
The meanings of edge offset signs are
illustrated
4Slide13
Contd..
Gibbs
phenomenon
can
be used to simulate a
few video compression
artifacts, especially the ringing
artifacts.
The dotted curve
-
original
samples
The solid curve -
reconstructed samples by discarding high frequencies of the original samplesSlide14
b) Band offset mode
In
the
band offset
mode
:
The selected offset value directly depends on the sample amplitude.
The full sample amplitude range is uniformly split into 32 segments called bands.
The sample values belonging to four of these bands (which are consecutive within the 32 bands) are modified by adding transmitted values
.Slide15
For example 8-bit samples ranging from 0 to 255, the width of a band is 8, and sample values from 8
k
to 8
k
+ 7 belong to band
k
.
The main reason for using four consecutive bands is that in the smooth areas artifacts can appear. Another reason is the number of bands in BO should be
equal to the number of signaled offsets in EO
Fig 6Slide16
Example of BO
The dotted curve is
the original
samples, while the solid curve is the
reconstructed samples corrupted
by
quantization
errors and
phase shifts
due to coded
motion vectors
deviating from the true motions.
In this example, the reconstructed
samples are shifted to the left of the original samples, which systematically results in
negative errors
that can
be corrected by BO for bands
k
,
k
+ 1,
k
+ 2,
and
k
+ 3.
7Slide17
Implementation
A. Fast Edge Offset Sample
Classification
A fast algorithm can be described in the following equations: [5]
sign3(
x
) = (
x >
0)?(+1) : ((
x
== 0)?(0) : (−1)) ……………..(1)
edgeIdx = 2 + sign3(
c − a) + sign3(
c
−
b
) .…………….(2)
edge
Idx
2category[] = {1, 2, 0
,
3
,
4} ….………….(3)
category = edgeIdx2category[edgeIdx]
. ………………(4)
Also, data reuse between samples can be further applied for the next sample classification. For example, assuming the EO class is 0 (i.e., using 1-D horizontal pattern) and the samples in the CTB are processed in the raster scan order, the sign3(c–a) of the current sample does not have to be calculated and can be directly set to the −sign3(
c–b
) of the neighboring sample to the left.
Likewise, the sign3(
c–b
) of the current sample can be reused by the neighboring sample to the right.Slide18
B. Fast Band Offset Sample Classification
The sample range is equally divided into 32 bands in BO
.
Since 32
=2^5,
the BO
sample classification
can be implemented as using the five
most significant
bits of each sample as the classification result
.
In this
way, the complexity of BO becomes very low, especially in hardware that only needs wire connections without logic gates
to obtain the classification result from the sample valueSlide19
C.
Fast
Distortion Estimation
To reduce the memory access and
operations, a
fast distortion estimation method
[
6
]
can be
implemented as follows
Let
k= sample positions, s(k)= original samples, and x
(k)= pre-SAO samples.where k
belongs to
C
and
C
is the set of samples that are inside a CTB
and belong to a specified SAO type (i.e., BO or EO), a
specified starting band position or EO class, and a specified band or category. The distortion between original samples and
pre- SAO
samples can be described in the following equation
:
The distortion between original samples and post-SAO
samples
In (6), h is the offset for the sample set.Slide20
The
delta
distortion is
defined in the following
equation
In
(7),
N
is the number of samples in the set, and
E
is the
sum of
differences between original samples and pre-SAO
samples .It is as defined in the following equation:
Next, the delta rate-distortion cost is defined in
the following
equation
:
In
(9),
λ
is the Lagrange multiplier, and
R
represents
the estimated number of
bits of side information.
For a given CTB with a specified SAO type (i.e., BO or EO), a specified starting band position or EO class, and
a specified
band or category, a few
h
values (i.e., offsets)
close to
the value of
E/N
are tested, and the offset that
minimizes
Δ
J
will be chosen.Slide21
Test Sequences [27]
BasketballPass_416x240_50.yuv
RaceHorses_832x480_30.yuv
RaceHorses_416x240_30.yuv
SlideEditing_1280x720_30Slide22
System Configuration
Operating System :
Windows 10 (64 bit)
RAM
: 16 Giga Bytes
Processor:
Intel Core i7 @ 2.60GHzSlide23
1)
SlideEditing_1280x720_30
sequences frame
100 [27]
(For 150 frames)
Fig. 8a
Original
Fig.8b
SAO=0
Fig.8c
SAO=1
ResultsSlide24
Metrics used
PSNR=20
MAX
f
is the maximum value of the sample.
The formula used for
Y’C
b
C
r
The format used is 4:2:0
Slide25
a) For Low Delay
QP=32
Total no.of Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV-PSNR
(dB)
Time
(s)
SAO=0
150
226.2496
37.0789
38.4938
38.2536
37.4580
2775.437
SAO=1
150
231.3856
37.9428
38.68
38.4851
38.1344
2872.767
b) For Random Access Mode
QP=32
Total
no.of Frames
Bit-Rate
(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV-PSNR
(dB)
Time
(s)
SAO=0
150
792.2064
38.1147
38.9933
39.0302
38.3711
2074.489
SAO=1
150
800.3808
38.8229
39.1529
39.2824
38.93
2155.361
c) For Intra Mode
QP=32
Total
no.of Frames
Bit-Rate(Kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV-PSNR
(dB)
Time (s)SAO=015019746.833637.115338.362138.293737.48161109.533SAO=115019898.227237.538938.603838.587737.86221270.508
SAO=1 is SAO filter ON
SAO=0
is SAO filter
OFFSlide26
2) BasketballPass_416x240_50.yuv
sequences frame 14
(Performed for 250 Frames
)
Fig.
9a
Original Image
Fig.
9b
SAO=0
Fig.9c
SAO=1
SAO=1 is SAO filter ON
SAO=0
is SAO filter
OFFSlide27
a)Random access
QP=32
Total
no.of Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV-PSNR
(dB)
Time(s)
SAO=0
250
328.5632
33.6028
39.2869
38.1648
34.5805
492.200
SAO=1
250
328.0144
33.7665
39.4510
38.2821
34.7336
513.282
QP=16
Total no.of
Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV-PSNR
(dB)
Time(s)
SAO=0
250
2664.3136
45.0055
47.0751
46.8594
45.4243
854.700
SAO=1
250
2666.6464
45.1293
47.2101
46.9925
45.5471
923.588
QP=50
Total no.of
Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR (dB) YUV-PSNR (dB) Time(s) SAO=025024.753624.8426633.234531.234526.1072349.368SAO=1250 24.425624.975733.308631.649726.2522359.752SAO=1 is SAO filter ONSAO=0 is SAO filter OFFSlide28
b)Intra mode
QP=32
Total
no.of Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV-PSNR
(dB)
Time(s)
SAO=0
250
1831.3024
35.684739.5170
38.081836.5370
210.334
SAO=1
250
1814.0704
35.5083
39.2031
38.7501
36.3379
157.469
QP=16
Total
no.of Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV- PSNR
(dB)
Time(s)
SAO=0
250
9670.1872
47.2712
48.5469
48.7344
47.6645
264.787
SAO=1
250
9683.3632
47.2761
48.3642
48.4900
47.6068
282.181
QP=50
Total
no.of Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR (dB)
YUV-PSNR (dB) Time(s) SAO=0250156.638425.639232.922331.678726.8699112.349SAO=1250 157.990425.825533.090431.954027.0568114.455SAO=1 is SAO filter ONSAO=0 is SAO filter OFFSlide29
c) Low Delay
QP=32
Total
no.of Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV-PSNR
(dB)
Time(s)
SAO=0
250
355.1632
33.2879
38.5792
37.5337
34.2023
705.907
SAO=1
250
353.0560
33.4710
38.7152
37.6405
34.3731
717.791
QP=16
Total
no.of Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV-PSNR
(dB)
Time(s)
SAO=0
250
2965.0272
45.0539
46.7155
46.7540
45.4664
1128.014
SAO=1
250
2965.5552
45.1017
46.8961
46.9131
45.5427
1189.622
QP=50
Total
no.of Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR (dB) YUV-PSNR (dB) Time(s) SAO=025024.569624.213532.901330.767825.4885500.357SAO=125024.409624.365432.930930.817025.6272540.829SAO=1 is SAO filter ONSAO=0 is SAO filter OFFSlide30
3)
RaceHorses_832x480_30.yuv sequences frame 1
Fig.10a
Original ImageSlide31
Fig.10b
SAO=0
SAO=1 is SAO filter ON
SAO=0
is SAO filter
OFFSlide32
Fig.10c
SAO=1
SAO=1 is SAO filter ON
SAO=0
is SAO filter
OFFSlide33
a)Random Access
(
i
)
Resolution
416x240_30
QP=32
Total
no.of Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV-PSNR
(dB)
Time(s)
SAO=0
150308.076831.5855
36.9274
37.7682
32.7045
360.327
SAO=1
150
306.6688
31.7813
37.0489
37.9131
32.8830
399.502
QP=32
Total
no.of Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV-PSNR
(dB)
Time(s)
SAO=0
150
1136.4832
31.6216
36.7789
38.3628
32.6673
1606.05
SAO=1
150
1126.5088
31.8225
36.9250
38.5497
32.8483
1949.06
(ii)
Resolution
832x480_30
SAO=1 is SAO filter ON
SAO=0
is SAO filter
OFFSlide34
QP=32
Total
no.of Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV-PSNR
(dB)
Time(s)
SAO=0
150
6568.1328
34.2315
37.2085
39.0594
35.0765
432.948SAO=1
150
6591.0240
34.3946
37.4344
39.3998
35.2511
439.159
b)Intra Mode
QP=32
Total
no.of Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV-PSNR
(dB)
Time(s)
SAO=0
150
1592.8960
33.7275
37.2400
38.2957
34.6544
118.810
SAO=1
150
1601.7280
33.8923
37.5336
38.6716
34.8426
123.505
(
i
) Resolution 416x240_30
(ii) Resolution 832x480_30
SAO=1 is SAO filter ON
SAO=0
is SAO filter
OFFSlide35
QP=32
Total
no.of Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV-PSNR
(dB)
Time(s)
SAO=0
150
323.3968
31.4442
36.5637
37.2843
32.5057
575.604SAO=1
150
320.1264
31.6196
36.6517
37.4310
32.6701
589.361
c) Low Delay
(
i
) Resolution 416x240_30
(ii) Resolution 832x480_30
QP=32
Total
no.of Frames
Bit-Rate(kbps)
Y-PSNR
(dB)
U-PSNR
(dB)
V-PSNR
(dB)
YUV-PSNR
(dB)
Time(s)
SAO=0
150
1200.0992
31.6915
36.4951
38.0022
32.6533
2202.56
SAO=1
150
1189.1056
31.8546
36.5840
38.2545
32.8089
2564.91
SAO=1 is SAO filter ON
SAO=0
is SAO filter
OFFSlide36
SAO Filter Code [28]
Void
TComSampleAdaptiveOffset
::
invertQuantOffsets
(
ComponentID
compIdx
,
Int
typeIdc, Int typeAuxInfo, Int* dstOffsets
, Int* srcOffsets)
{
Int
codedOffset
[MAX_NUM_SAO_CLASSES];
::memcpy(codedOffset
,
srcOffsets
,
sizeof
(Int)*MAX_NUM_SAO_CLASSES); ::
memset(dstOffsets, 0, sizeof
(Int)*MAX_NUM_SAO_CLASSES); if(typeIdc
==
SAO_TYPE_START_BO)
{
for(Int i=0; i< 4; i++)
{
dstOffsets
[(
typeAuxInfo+i
)%NUM_SAO_BO_CLASSES
]=
codedOffset
[(
typeAuxInfo+i
)%NUM_SAO_BO_CLASSES]*(1<<m_offsetStepLog2[
compIdx
]);
}
}
else //
EO{
for(
Int
i
=0;
i
< NUM_SAO_EO_CLASSES;
i
++)
{
dstOffsets
[
i
] =
codedOffset
[
i
] *(1<<m_offsetStepLog2[
compIdx
]);
}
assert(
dstOffsets
[SAO_CLASS_EO_PLAIN] == 0); //keep EO plain offset as zero
}Slide37
Contd..
switch(
typeIdx
)
{
case SAO_TYPE_EO_0:
{
offset
+= 2;
startX = isLeftAvail ? 0 : 1;
endX = isRightAvail ? width : (width -1);
for
(y=0; y<
height
; y
++)
{ signLeft
= (
SChar
)
sgn
(srcLine[startX] - srcLine[startX-1]);
for (x=startX
; x< endX; x++){
signRight
= (
SChar
)
sgn
(
srcLine
[x] -
srcLine
[x+1]);
edgeType
=
signRight
+
signLeft
;
signLeft
= -
signRight
;
resLine
[x] = Clip3<
Int
>(0,
maxSampleValueIncl
,
srcLine
[x] + offset[
edgeType
]);
}
srcLine
+=
srcStride
;
resLine
+=
resStride
;
}
}
break;
.
.
.Fig 11. [2]Slide38
Contd..
case
SAO_TYPE_BO
:
{
const
Int
shiftBits
= channelBitDepth - NUM_SAO_BO_CLASSES_LOG2; for (y=0; y< height; y++)
{ for (x=0; x< width; x++) {
resLine
[x] = Clip3<
Int
>(0,
maxSampleValueIncl
, srcLine[x] + offset[
srcLine[x] >> shiftBits] ); }
srcLine
+=
srcStride
; resLine += resStride;
} } break;
default: {
printf
("Not a supported SAO types\n");
assert(0);
exit(-1);
}}}
For BO, all pixels are processed
For
EO, pixel availability is checked according to SAO type and if pixel is not available in
boundary condition
it is skipped for processing (i.e., offset of 0 )Slide39
Conclusion
SAO locates after
deblocking
and is a
in-loop filtering
technique that reduces the distortion between
original
samples and reconstructed
samples.
It has been observed
that SAO
can improve video compression in both objective
and subjective measures with reasonable complexity.Different modes of configuration –Random access mode, Low delay mode and Intra mode configuration have been used for different test sequences of various complexity to implement the SAO filter.The bit-rate and PSNR have
been compared for these test sequences.Slide40
References
G.
J
. Sullivan et al, “Overview of the High Efficiency Video Coding (HEVC) Standard”,
IEEE
Trans.on
Circuits and Systems for Video Technology, Vol. 22, No. 12, pp. 1649-1668, Dec. 2012
.
C. –M. Fu
et al , Members of IEEE “Sample Adaptive Offset in the HEVC
Standard” IEEE Transactions on circuits and systems for video technology, vol. 22, No. 12,
Dec. 2012.
S
.
Srinivasan
et al , “Windows Media Video 9:Overview and applications,” Signal Process. Image
Commun
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19,no
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Zhang,
Zhi
Liu,
Jianfeng
Qu : “Sample Adaptive Offset Optimization in HEVC” , Sensors & Transducers, Vol 182
, Issue11,Nov.2014
, pp. 237-243
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offset for
HEVC,” in
Proc. IEEE 13th Int. Workshop MMSP
,
Oct
. 2011,
pp.1–5.
V. Sze and M.
Budagavi
, “Design and Implementation of Next Generation Video Coding Systems (H.265/HEVC Tutorial)”, IEEE International Symposium on Circuits and Systems (ISCAS), Melbourne, Australia, June 2014.
V
. Sze, M.
Budagavi
and G.J. Sullivan (Editors), “High Efficiency Video Coding (HEVC): Algorithms and Architectures”, Springer, 2014.
G. J. Sullivan et al, “Overview of the High Efficiency Video Coding (HEVC) Standard”, IEEE Trans. on Circuits and Systems for Video Technology, Vol. 22, No. 12, pp. 1649-1668, Dec. 2012.
I.E.G. Richardson, “Video Codec Design: Developing Image and Video Compression Systems”, Wiley, 2002.Slide41
Contd..
I.E.G. Richardson, “The H.264 advanced video compression standard”, 2nd Edition, Hoboken, NJ, Wiley, 2010.
K.
Sayood
, “Introduction to Data compression”, Third Edition, Morgan Kaufmann Series in Multimedia Information and Systems, San Francisco, CA, 2005
HEVC tutorial by I.E.G. Richardson:
http://www.vcodex.com/h265.html
A.Norkin
et.al, (2012) HEVC
deblocking
filtering and decisions. In: Proc. SPIE. 8499, Applications of Digital Image Processing XXXV, no. 849912, Oct. 2012
A.Norkin
,
K.Andersson
,
V.Kulyk
(2013) “Two HEVC encoder methods for block
artifact
reduction”. In: Proceedings of the IEEE international conference on visual communications and image processing (VCIP) 2013, Kuching, Sarawak, pp. 1–6, Nov. 2013
A.Norkin
,
K.Andersson
,
R.Sjöberg
(2013) AHG6: on deblocking filter and parameters signaling
, Joint Collaborative Team on Video Coding (JCT-VC), Document JCTVC-L0232, Geneva, Jan. 2013B.
Bross et al, High Efficiency Video Coding (HEVC) Text Specification Draft 8,
document JCTVC-J1003
,
Jul.2012.
Joint Video Team of ITU-T VCEG and ISO/IEC MPEG,
ITU-T
Rec.
H.264
, ISO/IEC 14496-10 AVC
, 2005
.
M. Yuen and H. R. Wu, “A survey of hybrid MC/DPCM/DCT
video coding
distortions,”
J. Signal Process.
, vol. 70, no. 3, pp. 247–278,
Nov.1998
.Slide42
Contd..
W.-S. Kim and D.-K. Kwon,
CE8 Subset c: Necessity of Sign Bits
for SAO
Offsets,
JCTVC-H0434, Feb.
2012.
G
.
Laroche
, T. Poirier, and P.
Onno
, On Additional SAO Band Offset Classifications, JCTVC-G246, Joint Collaborative Team on Video
Coding,Nov. 2011.
N.Ahmed
,
R.Natarajan
and
K.R.Rao
, “
DiscreteCosine Transform”, IEEE Trans. On Computers, Vol.C-23, pp.90-93, Jan.1974
E.
Maani
and O.
Nakagami, Flexible Band Offset Mode in SAO,document
JCTVC-H0406, Feb. 2012.K
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Merge up
Flags,
JCTVC-J0355, Joint Collaborative Team on Video Coding,
Jul.2012.
E
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Alshina
et al
,
AHG6
: On SAO Type Sharing Between U and V Components,
JCTVCJ0045,Joint
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.
Access to
HM
Software Manual:
http://iphome.hhi.de/marpe/download/Performance_HEVC_VP9_X264_PCS_2013_preprint.pdf
Test Sequences:
ftp://ftp.kw.bbc.co.uk/hevc/hm-11.0-anchors/bitstreams/
Access to HM
16.9
Reference Software:
http://hevc.hhi.fraunhofer.de
/Slide43
Contd..
HEVC tutorial by I.E.G. Richardson:
http://www.vcodex.com/h265.html
Multimedia
Course website-
http://
www.uta.edu/faculty/krrao/dip/Courses/EE5359/index_tem.html
Joint Collaborative Team On Video Coding Information website-
http://www.itu.int/en/ITU-T/studygroups/2013-2016/16/Pages/video/jctvc.aspx
MPL website
:
http://
www.uta.edu/faculty/krrao/dip/Slide44
THANK YOU