Distributed Video Coding Bernd Girod, Anne Margot Aaron, Shantanu Rane, and David Rebollo-Monedero...
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Transcript of Distributed Video Coding Bernd Girod, Anne Margot Aaron, Shantanu Rane, and David Rebollo-Monedero...
Distributed Video Coding
Bernd Girod, Anne Margot Aaron, Shantanu Rane, and David Rebollo-Monedero
IEEE Proceedings 2005
Outline
Foundations of Distributed Coding Low-Complexity Video Encoding
Foundations of Distributed Coding (1) What is distributed coding?
Coding of multiple dependent random sequences with separate encoders sending separate bit-streams to a single decoder.
Based Slepian-Wolf and Wyner-Ziv information-theoretic results
0 2 4
1 3 5
0 1 2 3 4
Encoder
Encoder
Decoder
Foundations of Distributed Coding (2) Slepian-Wolf Coder and Wyner-Ziv Coder
X and Y are very similar
Lossless coder
Side information
Foundations of Distributed Coding (3) Given two dependent i.i.d. random sequences X and Y.RX ≥ H(X), RY ≥ H(Y)
Slepian-Wolf theoremRX + RY ≥ H(X, Y)
RX ≥ H(X|Y), RY ≥ H(Y|X)
entropy
Joint entropy
encoding decoding
X
Y
X
Y
Foundations of Distributed Coding (4) Slepian-Wolf coding
Slepian-Wolf coder Encoder: Encoding X without Y Decoder: Reconstructing X with Y
Assumptions X and Y are very similar Y is known at the decoder
XChannelcoding XP
Y
PYP
Channeldecoding X
Parity bits
Alternative 2:encoder decoder
Slepian-Wolf encoder
Slepian-Wolf decoder
ABCABCABC
XA
ABCABCABC
YY
X
encoder decoder
Alternative 1:
Foundations of Distributed Coding (5) RD Theory for Lossy Compression with Re
ceiver Side InformationDistortionWyner-Ziv RD function
in the case of Gaussian memoryless sources and mean-squared error
distortion, or X is the sum of arbitrarily distributed Y and independent
Gaussian noise.
Y is known at the encoderY isn’t known at the encoder
Foundations of Distributed Coding (6) Wyner-Ziv Coding
Reconstruct with side information Y.Assumptions
Quantization step size Three interleaved quantizers: A, B, and C
A AB B CC
Y X
X
★ log23 bits
A AB B CC
X X A
Y
Encoder Decoder
(3/2)δ(3/2)δ
Low-Complexity Video Encoding (1) Conventional video encoder
5-10 times more complex than the decoder Suitable for the case that video is compressed once
and decoded many times Broadcasting or VOD systems
Distributed video encoder Low-complexity encoder, but high-complexity decoder Suitable for
Wireless video sensors for surveillance Wireless PC cameras Mobile camera phones Disposable video cameras
Low-Complexity Video Encoding (2) Pixel-Domain and Transform-Domain Encoding
A Laplacian distribution between S and is assumed
The Laplacian parameter is estimated from previous decoded frames
Encoding time (Pentimu III 1.2GHz) – pixel-domain encoding
Wyner-Ziv: 2.1 ms/frame H.263 I-frame: 36 ms/frame H.263 B-frame: 227 ms/frame
KeyFrame
W-ZFrame
W-ZFrame
W-ZFrame
KeyFrame
W-ZFrame
KeyFrame… …
S
Low-Complexity Video Encoding (3) Pixel-Domain and Transform-Domain
Encoding
Low-Complexity Video Encoding (4) Side information in decoder side
Copying from previous frames, motion-compensated interpolation, multiple frame predictors, …
e.g. Motions estimation at the decoder Additional information is helpful
CRC or some coefficients of the quantized symbol
CRC(0,0)
CRC(0,1)
CRC(0,2)
CRC(1,0)
CRC(1,1)
CRC(1,2)
CRC(2,0)
CRC(2,1)
CRC(2,2)
CRC(1,1)
previouscurrent
encoder decoder
Low-Complexity Video Encoding (4) Rate control
Controlled by the decoder Using a feedback channel Must be performed online useful information can help flexible generation of side
information through the feedback channel Controlled by the encoder
Classifying blocks into several modes with different rates Using the frame difference or block behavior
Better side information cannot lower the bit-rate Can be performed offline
Low-Complexity Video Encoding (5) Some topics about DVC
How to generate side information?Spatial domain or frequency domain?What is the optimal quantizer for DVC?Rate control in DVCRobust transmission…