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## Distributed Video Coding

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**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 1 3 5 Encoder Decoder Encoder 0 1 2 3 4 0 2 4**Foundations of Distributed Coding (2)**• Slepian-Wolf Coder and Wyner-Ziv Coder • X and Y are very similar Side information Lossless coder**Foundations of Distributed Coding (3)**• Given two dependent i.i.d. random sequences X and Y. • RX≥ H(X), RY ≥ H(Y) • Slepian-Wolf theorem • RX +RY ≥ H(X, Y) • RX≥ H(X|Y), RY ≥ H(Y|X) entropy Joint entropy X X Y Y encoding decoding**Foundations of Distributed Coding (4)**Slepian-Wolf encoder Slepian-Wolf decoder • 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 encoder decoder A X Y B C B C B C X A A A Y Alternative 2: encoder decoder A B C B C B C A A P Alternative 1: Channel coding Channel decoding X XP YP X Parity bits Y**Foundations of Distributed Coding (5)**• RD Theory for Lossy Compression with Receiver Side Information • Distortion • Wyner-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. Yisn’tknown at the encoder Y is 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 ★log23 bits Encoder Decoder X Y A (3/2)δ (3/2)δ Y B C B C B C B C A A A A**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 Key Frame W-Z Frame W-Z Frame Key Frame W-Z Frame W-Z Frame Key Frame … …**Low-Complexity Video Encoding (3)**• Pixel-Domain and Transform-Domain Encoding**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) 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 previous current CRC (1,1) 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 DVC • Robust transmission • …