Brief Overview of Wyner-Ziv CODEC
and Research Plan
Jin-soo KIM
Contents

Overview of Wyner-Ziv CODEC




Application of Wyner-Ziv CODEC
Basic Principle of WZ CODEC
Generation of S.I. at the Decoder
How to Encode WZ frames
Research Plan
 Q&A
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J.S.Kim
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Application of WZ CODEC
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Video coding : history and trends
2010
2005
H.265(?)
HDTV
2003 H.264
SVC
mobile
Mobile TV
1999
MPEG4
Hand PC
Video Conferencing
H.263
MPEG2
Mobile Phone
1994
1992
MPEG1
Mobile : 3low1high
Year
• Low (battery, bandwidth, CPU)
• High cost
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(Conventional) Interframe Video Coding
Predictive
Interframe
Encoder
X
Predictive
Interframe
Decoder
Y
Y
X’
Side Information
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Low Complexity Encoder
Wyner-Ziv
Intraframe
Encoder
Wyner-Ziv
Interframe
Decoder
X
Y
X’
Side Information
[Witsenhausen, Wyner, 1980]
[Puri, Ramchandran, Allerton 2002]
[Aaron, Zhang, Girod, Asilomar 2002]
…
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J.S.Kim
Applications of WZ codec

Light encoder and light decoder
B. Girod, A. Aaron, S. Rane, D. Rebollo-Monedero, “Distributed video coding,” Proceedings of the IEEE, Vol93, pp71-83, Jan. 2005.
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Applications of WZ codec
http://www.discoverdvc.org/deliverables/Discover-D4.pdf
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Wireless low power video surveillance
Disposable video cameras
Sensor network
Multi-view image acquisition
Medical applications
Networked camcoders
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Applications of WZ codec
http://www.discoverdvc.org/deliverables/Discover-D4.pdf

SensorCamPillCamWearableCamDispos
able cam.ScanCam
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
Basic Principle of WZ CODEC
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J.S.Kim
Lossless Compression
with Side Information
R ≥ H(X|Y)
X
Statistically
dependent
Encoder
Y
Decoder
X
Y
Side Information
Wyner-Ziv showed that the conditional rate-mean squared error distortion function for X is the
same whether the side information Y is available only at the decoder, or both at the encoder
and the decoder.
R ≥ H(X|Y)
X
Encoder
Decoder
Statistically
dependent
Side Information
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Y
X
[Slepian, Wolf, 1973]
J.S.Kim
Shannon Theory with side info.

Example) x : dice number

H(X) = 6Σlog26 = 2.58 bits

Shannon coding theorem


X
encoder R decoder
X
Y
No error, if H(X) < R(X) = 3 bits
If R(X) = 2, {00,01,10,11}{1,2,{3,4},{5,6}}
Information loss

With side information Y=“even number”

H(X|Y) = 3Σlog23 = 1.58 < R(X|Y) = 2
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J.S.Kim
Wyner-Ziv coding (lossy)
A. Majumdar, R. Puri, P. Ishwar, K. Ramchandran, “Complexity/performance trade-offs for robust distributed video coding,” IEEE ICIP2005, Vol.
2, pp678-81, 11-14 Sept. 2005
•
•
•
WZ = quantization + Slepian-Wolf
Random coset partitioning operation,
3bit-info can be represented by 2bit (LSB first  increase Δ)
• X : original value
U : quantized value
• Y : side information in the decoder
• given Y + sent 10U=101
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J.S.Kim
History of DVC

Slepian and Wolf : lossless DVC (1973)
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
Wyner and Ziv : lossy DVC (1976)

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Power-efficient, Robust, hIgh-compression, Syndrome-based Multimedia coding
Girod in Stanford : Good review (2005)


“The rate-distortion function for source coding with side information at the decoder,” IEEE Tr. Information
Theory, 1976.
Ramchandran in Berkeley : PRISM (2002)


“Noiseless coding of correlated information sources,” IEEE Tr. On Information Theory, 1973.
“Distributed video coding,” IEEE Proceedings, 2005.
EU : DISCOVER(~2006), www.discoverdvc.org

DIStributed COding for Video sERvices
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J.S.Kim
Towards Practical Slepian-Wolf Coding
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Convolution coding for data compression [Blizard, 1969]
Convolutional source coding [Hellman, 1975]
Syndrome source coding [Ancheta, 1976]
Coset codes [Pradhan and Ramchandran, 1999]
Trellis codes [Wang and Orchard, 2001]
Turbo codes
[García-Frías and Zhao, 2001]
[Bajcsy and Mitran, 2001]
[Aaron and Girod, 2002]
LDPC codes [Liveris, Xiong, and Georghiades, 2002]
...
...
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
Generation of S.I. at the Decoder
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Motion Compensation

Motion-compensated interpolation (MC-I)
using the decoded Key frame at time t-1 & t+1
Estimate the motion
t-1
Key Frame
t
t+1
Wyner-Ziv
Frame
Key Frame
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J.S.Kim
Side Information
Key Frame
Conventional
Intraframe
codec
K1
K1'
Reconstructed
Key Frame
Side
Information
Wyner-Ziv
Frame
S2
Interpolation
S2
Side
Information
Wyner-Ziv
Frame
S3
Interpolation
S3
S3'
Reconstructed
WZ Frame
Side
Information
Wyner-Ziv
Frame
S4
Key Frame
K5
Wyner-Ziv
Decoder
Conventional
Intraframe
codec
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Interpolation
K5'
S4
Reconstructed
Key Frame
J.S.Kim
Motion Compensation

Motion-compensated extrapolation (MC-E)
estimate the motion between the Wyner-ziv frame a
t time t-2 and the Key frame at time t-1
Estimate the motion
t-2
t-1
t
Wyner-Ziv
Frame
Key Frame
Wyner-Ziv
Frame
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J.S.Kim
Side Information
Key Frame
K1
Conventional
Intraframe
codec
K1'
Reconstructed
Key Frame
S2'
Reconstructed
WZ Frame
Side Information
Wyner-Ziv
Frame
S2
Extrapolation
S2
Wyner-Ziv
Decoder
Wyner-Ziv
Frame
S3
Extrapolation
S3
S3'
Reconstructed
WZ Frame
Wyner-Ziv
Decoder
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J.S.Kim
Motion Compensation
1 WZ Frame : K1 - S2 - K 3
3 WZ Frame : K1 - S2 - S3 - S4 - K 5
1
S 2  MCI ( K , K , )
2
1
S 3  MCI ( K , K , )
2
^
'
' 1
S 2  MCI ( K1 , S3 , )
2
^
'
' 1
S 4  MCI ( S 3 , K 5 , )
2
^
'
1
'
3
2 WZ Frame : K1 - S2 - S3 - K 4
1
S 2  MCI ( K1' , K 4' , )
3
^
2
S 3  MCI ( K1' , K 4' , )
3
^
^
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'
1
'
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J.S.Kim

How to Encode WZ frames
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J.S.Kim
Wyner-Ziv Residual Video Codec
WZ frames
W
X
WZ
Decoder
WZ
Encoder
Xer
•
•
Xer
X’
Y
Residual of a frame with respect to an encoder reference frame (Xer) is fed into a Wyner-Ziv
encoder. To avoid drift, Xer should be replicable at the decoder.
Since the decoder takes into account motion, Y is expected to be a better estimate of frame X
than Xer. The Wyner-Ziv decoder uses both Y and Xer to calculate the reconstruction X’.
[Aaron, Zhang, Girod, Asilomar 2002]
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J.S.Kim
Pixel-Domain Wyner-Ziv Video Codec
Interframe Decoder
Intraframe Encoder
Slepian-Wolf Codec
WZ frames
Scalar
Quantizer
W
Turbo
Encoder
Turbo
Decoder
Buffer
Reconstruction
W’
Request bits
Side
Y
informati
on
Interpolation/
Extrapolation
Key frames
I
Conventional
Intraframe
decoding
Conventional
Intraframe coding
I’
[Aaron, Zhang, Girod, Asilomar 2002]
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J.S.Kim
Pixel-Domain Wyner-Ziv Video Codec
After Wyner-Ziv Decoding
Decoder side information
generated by motioncompensated interpolation
PSNR 24.8 dB
16-level quantization – 2.0 bpp
0 pixels in error
PSNR 36.5 dB
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[Aaron, Zhang, Girod, Asilomar 2002]
J.S.Kim
DCT-Domain Wyner-Ziv Video Codec
Intraframe Encoder
Interframe Decoder
WZ frames
Dk’
Dk
W
DCT
Scalar
Quantizer
Turbo
Encoder
Request bits
For each transform band k
Buffer
Turbo
Decoder
Recon
W’
IDCT
Side information
Yk
DCT
Y
Interpolation/
Extrapolation
Key frames
I
Conventional Intraframe
coding
Conventional
Intraframe
decoding
I’
[Aaron, Zhang, Girod, Asilomar 2003]
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J.S.Kim
Rate-Distortion Performance - Salesman
Encoder Runtime
Pentium 1.73 GHz machine
B frame ~ 100%
Interframe
100%
3 dB
WZ DCT ~ 7%
WZ Pixel ~ 6%
6 dB
I frame ~ 18%
Every 8th frame is a key frame
Salesman QCIF sequence at 10fps
100 frames
[Aaron, Zhang, Girod, Asilomar 2003]
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J.S.Kim
Salesman at 10 fps
DCT-based Intracoding 149 kbps
PSNRY=30.0 dB
Wyner-Ziv DCT codec 152 kbps
PSNRY=35.6 dB GOP=8
[Aaron, Zhang, Girod, Asilomar 2003]
Conclusion

Increase efficiency of DVC



Reduce H(X) : simple ME/MC?
Increase H(Y) : better interpolation/extrapolation
Stronger correlation between X and Y.
X
encoder
R
decoder
X
Y
X? Y? P(X/Y)
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J.S.Kim
Conclusion

Distributed coding is a fundamentally new paradigm for video co
mpression

Slepian-Wolf encoding, is fundamentally harder for practical appli
cations due to the general statistics of the correlation channel

The rate-distortion performance of Wyner-Ziv coding does not yet
reach the performance of conventional interframe coder

It is unlikely that distributed video coding algorithm will ever beat
conventional video coding schemes in R-D performance

Many authors believe that distributed coding techniques will soon
complement conventional video coding to provide the best overal
l system performance and enable novel applications
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
Research Plan (with M.S. Vidhya Murthy)
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J.S.Kim
Research Plan
Plan
done
■ Plan and achievements
plan
(Aug.2008 – June 2009)
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9
10
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12
1
2
3
4
5
6
▣ Simulation Environment and survey WZ CODEC
- survey WZ CODEC
- joint simulation model of H.264 CODEC
▣ Survey of Channel Coding Algorithm
- channel coding/decoding algorithm
- analysis of channel source code
▣ Implementation of Wyner-Ziv CODEC
- Performance comparison of Pixel- and Transform-domain
- Investigate the statistical characteristics and distributions of
the residual signal
- Efficient encoding algorithm (Quantization/Entropy coding or
Slepian-Wolf encoding/decoding)
- Efficient generation of Side Information
- Implementation of channel encoding/decoding algorithm
- Rate control (or buffer control) algorithm
Now
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J.S.Kim

Q&A
Thank you
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J.S.Kim