Reinventing Compression: The New Paradigm of Distributed Video Coding

1
Reinventing CompressionThe New Paradigm
ofDistributed Video Coding
Bernd Girod Information Systems
Laboratory Stanford University
2
Outline

• Lossless and lossy compression with receiver side
  information
• Shifting the complexity of video encoding to the
  decoder
• Error-resilient video transmission
• Image authentication

3
Outline

• Lossless and lossy compression with receiver side
  information
• Shifting the complexity of video encoding to the
  decoder
• Error-resilient video transmission
• Image authentication

4
Lossless Compression with Side Information
R H(XY)
Encoder
Decoder
Statistically dependent
Side Information
R ?
Encoder
Decoder
Statistically dependent
Side Information
5
Lossless Compression with Side Information
R H(XY)
Encoder
Decoder
Statistically dependent
R H(XY)
Encoder
Decoder
Statistically dependent
Slepian, Wolf, 1973
6
Towards Practical Slepian-Wolf Coding

• 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
• . . .
• . . .

7
Rate-Adaptive Slepian-Wolf Coding
Parity bits
Request bits
L 8192 bits Total simulated bits 226
8
Lossy Compression with Side Information
RXY (d)
Encoder
Decoder
Wyner, Ziv, 1976 For MSE distortion and
Gaussian statistics, rate-distortion functions
of the two systems are the same.
Zamir, 1996 The rate loss R(d) RXY (d) is
bounded.
R(d)
Encoder
Decoder
9
Practical Wyner-Ziv Coding
Wyner-Ziv Decoder
Wyner-Ziv Encoder
Slepian- Wolf Decoder
Minimum Distortion Reconstruction
Slepian-Wolf Encoder
Quantizer
10
Non-Connected Quantization Regions

• Example Non-connected intervals for scalar
  quantization
• Decoder Minimum mean-squared error
  reconstruction with side information

x
x
11
Outline

• Lossless and lossy compression with receiver side
  information
• Shifting the complexity of video encoding to the
  decoder
• Error-resilient video transmission
• Image authentication

12
Interframe Video Coding
PredictiveInterframe Encoder
PredictiveInterframe Decoder
X
Side Information
13
Low Complexity Encoder
Wyner-ZivIntraframe Encoder
Wyner-ZivInterframe Decoder
X
Side Information
Witsenhausen, Wyner, 1980 Puri, Ramchandran,
Allerton 2002 Aaron, Zhang, Girod, Asilomar
2002
14
(No Transcript)
15
Pixel-Domain Wyner-Ziv Video Codec
Interframe Decoder
Intraframe Encoder
WZ frames
Slepian-Wolf Codec
Reconstruction
Turbo Encoder
Turbo Decoder
Scalar Quantizer
X
X
Buffer
Request bits
Side information
Y
Interpolation/ Extrapolation
Key frames
Conventional Intraframe decoding
Conventional Intraframe coding
I
I
Aaron, Zhang, Girod, Asilomar 2002
16
Pixel-Domain Wyner-Ziv Video Codec
After Wyner-Ziv Decoding
Decoder side informationgenerated by
motion-compensated interpolationPSNR 30.3 dB
16-level quantization 1.375 bpp11 pixels in
errorPSNR 36.7 dB
17
Pixel-Domain Wyner-Ziv Video Codec
After Wyner-Ziv Decoding
Decoder side informationgenerated by
motion-compensated interpolationPSNR 24.8 dB
16-level quantization 2.0 bpp0 pixels in
errorPSNR 36.5 dB
18
DCT-Domain Wyner-Ziv Video Codec
Interframe Decoder
Intraframe Encoder
WZ frames
Xk
Xk
Recon
Scalar Quantizer
Turbo Encoder
Turbo Decoder
W
W
IDCT
DCT
Buffer
Request bits
Side information
Yk
For each transform band k
DCT
Y
Interpolation/ Extrapolation
Key frames
Conventional Intraframe decoding
Conventional Intraframe coding
I
I
19
Rate-Distortion Performance - Salesman
Encoder Runtime
Pentium 1.73 GHz machine

• Every 8th frame is a key frame
• Salesman QCIF sequence at 10fps 100 frames

20
Rate-Distortion Performance Hall Monitor

• Every 8th frame is a key frame
• Hall Monitor QCIF sequence at 10fps 100 frames

21
Salesman at 10 fps
DCT-based Intracoding 149 kbps PSNRY30.0 dB
Wyner-Ziv DCT codec 152 kbps PSNRY35.6 dB
GOP8
22
Hall Monitor at 10 fps
DCT-based Intracoding 156 kbps PSNRY30.2 dB
Wyner-Ziv DCT codec 155 kbps PSNRY37.1 dB
GOP8
23
Outline

• Lossless and lossy compression with receiver side
  information
• Shifting the complexity of video encoding to the
  decoder
• Error-resilient video transmission
• Image authentication

24
Systematic Lossy Source/Channel Coding

• Information theoretic optimality conditions
  Shamai, Verdú, Zamir, 1998
• Enhancing analog image transmission using digital
  side information
• Pradhan, Ramchandran, 2001
• Lossy source-channel coding of video waveforms
• Rane, Aaron, Girod, 2004,05,06

25
Systematic Lossy Error Protection (SLEP)
Analog Channel
Video With Errors
Video Encoder
Video Decoder With Error Concealment
Input Video
Channel
Side Information
Wyner-Ziv Encoder
Wyner-Ziv Decoder
Output Video
26
SLEP using H.264/AVC Redundant Slices
H.264/AVC DECODER
H.264/AVC ENCODER
Output Video
Input Video
Entropy Decoding
Encode Primary Pic

T-1
MC
Motion Vecs Coding Modes
Motion Vecs Coding Modes
Encode Redundant Pic (Requantize)
Encode Redundant Pic (Requantize)
Error-prone Channel
Side info
QP
Decode Redundant Slice
Erasure Decoding
Parity Slices QP
RS Encoder
27
Foreman _at_ 408 kbps, error resilience bit rate
40 kbps Symbol error probability 5 x 10-4
Error-free
After error propagation
QP 28 35.7 dB
Error concealment only
40 kbps FEC
SLEP with redundant QP 36
SLEP with redundant QP 40
SLEP with redundant QP 48
20.9 dB
25.5 dB
30.9 dB
34.2 dB
32.9 dB
28
Foreman _at_ 1 Mbps Symbol error probability 2 x
10-4
100 kbps FEC PSNR 32.5 dB Recovered 53.7
of lost macroblocks
100 kbps Wyner-Ziv bit stream PSNR 38.0
dB Recovered 96.6 of lost macroblocks
29
Rally, 1 Mbps, 3 packet loss
80 kbps FEC 33.4 dB
80 kbps Wyner-Ziv bit stream 38.1 dB
Recovered 67.5 of lost macroblocks
Recovered 97.1 of lost macroblocks
30
Outline

• Lossless and lossy compression with receiver side
  information
• Shifting the complexity of video encoding to the
  decoder
• Error-resilient video transmission
• Image authentication

31
Media Authentication Problem
Received
Illegimate degradation (e.g., compression
tampering)
Original
Legimate degradation (e.g., compression)
How to distinguish legimate and illegimate signal
degradationswithout access to the original?
32
Image Authentication by Distributed Coding
Received
Original
?
Side information
Slepian-Wolf coder
Slepian-Wolf decoder
Coarse approximation or (random) projection
Lin, Varodayan, Girod, ICIP 2007 Lin,
Varodayan, Girod, MMSP 2007
33
Image Authentication by Distributed Coding
Received
Original
?
Side information
Slepian-Wolf coder
Slepian-Wolf decoder
Coarse approximation or (random) projection
Lin, Varodayan, Girod, ICIP 2007 Lin,
Varodayan, Girod, MMSP 2007
34
Image Authentication by Distributed Coding
Lin, Varodayan, Girod, ICIP 2007
35
Minimum Rate for Successful Decoding
Experiment JPEG or JPEG2000 compression
illegimate text banner
Lin, Varodayan, Girod, ICIP 2007
36
Demo
37
Distributed Image/Video CodingWhy Do We Care?

• New Paradigm Chance to Reinvent Compression from
  Scratch
• Entropy coding
• Quantization
• Signal transforms
• Adaptive coding
• Rate control
• . . .
• Powerful New Tool in the Compression Tool-Box
• Very low complexity encoders
• Compression for networks of cameras
• Error-resilient transmission of signal waveforms
• Digitally enhanced analog transmission
• Unequal error protection without layered coding
• Image authentication
• Random access
• Compression of encrypted signals
• . . .

38
Further interest

• B. Girod, A. Aaron, S. Rane, D. Rebollo-Monedero,
  "Distributed Video Coding," Proceedings of the
  IEEE, Special Issue on Video Coding and Delivery.
  January 2005. http//www.stanford.edu/bgi
  rod/pdfs/DistributedVideoCoding-IEEEProc.pdf