Abhik Majumdar, Rohit Puri, Kannan Ramchandran, and Jim Chou

1
Distributed Video Coding and Its Application

• Abhik Majumdar, Rohit Puri, Kannan Ramchandran,
  and Jim Chou

Presented by Lei Sun
2
Introduction(1/3)

• Contemporary digital video coding architectures
  have been driven primarily by the downlink
  broadcast model of a complex encoder and
  multitude of light decoders. However, with the
  current proliferation of video devices which have
  constrained computing ability, memory and battery
  power, we expect future systems to use multiple
  video input and output streams captured using a
  network of distributed devices and transmitted
  over a bandwidth-constrained, noisy wireless
  transmission medium.

3
Introduction(2/3)

• System requirements
• robustness to packet/frame loss caused by channel
  transmission errors
• low-power and light-footprint encoding due to
  limited battery power and/or device memory
• high compression efficiency due to both bandwidth
  and transmission power limitation.

4
Introduction(3/3)

• PRISM (a video coding paradigms founded on the
  principles of source coding with side
  information)
• A flexible distribution of computational
  complexity between encoder and decoder
• High compression efficiency

5
Background on Source Coding with Side Information
(1/3)

• Let 3bits binary data X, Y can have the same
  possibilty of 8 values. they are correlated so
  the Hamming distance is at most 1. there are 2
  scenario showed in figure 1

Scenario a X can be encoded in 2 bits using
(X?Y) since Y is available both on encoder and
decoder.
Figure 1
Scenario b Y is only available on decoder, X
encoded in to a coset index so the decoder
reception coset index using Y.
6
Background on Source Coding with Side Information
(2/3)

• compressing the two or more sources seperately
  and decoding using the correlation between these
  sources
• Slepian and Wolf theorem (lossless case)
• Wyner-Ziv theorem (lossy case)

7
Background on Source Coding with Side Information
(3/3)

• Figures 2,4 show the structure of the Wyner-Ziv
  encoding and decoding

Figure 2 (a) Encoding consists of quantization
followed by a binning operation encoding U into
Bin (Coset) index.
8
(b) Structure of distributed decoders. Decoding
consists of de-binning followed by estimation.
Figure 3
(c) Structure of the codebook bins.
9
Architectural Goals of PRISM

• Compression Performance
• The current macro-block X can be encoded into bin
  index which reduces the encoding rate.
• Robustness
• As long as Y-Xltd (step size), the decoder is
  guaranteed to recover the correct output.
• Moving Motion-Search Complexity to the Decoder
• Uncertainty at the receiver about the exactly
  state of the side information that requires
  Motion-search at the decoder.

10
A Theory for Distributed Video Coding

• Sharing Motion Complexity between Encoder and
  Decoder
• A Motion-Compensated Video model

Figure 4 Motion-indexed additiveinnovations
model for video signals. X denotes a block of
size n pixels in the current frame to be encoded
and Y1,Y2Ym is the set of blocks (each of size
n) in the previous decoded frame corresponding to
different values of the motion vector indexed by
T.
11
Sharing Motion Complexity between Encoder and
Decoder

• Motion-Compensated Predictive Coding
• Step1The encoder estimates and transmits the
  index of the estimated motion vector to the
  decoder.
• Step 2 Once the decoder knows T , the video
  coding problem is reduced to the problem of
  compressing the source X using the correlated
  side-information YT now available to both the
  encoder and the decoder.

12
Sharing Motion Complexity between Encoder and
Decoder

• Distributed Video Coding
• In this case, due to severely limited processing
  capability (or some other reason), the encoder is
  disallowed from performing the complex
  motion-compensated prediction task. This is in
  effect pretending that the encoder does not have
  access to the previous decoded blocks Y1, . . .
  ,YM.

13
A Theory for Distributed Video Coding

• Robustness to Transmission Errors
• Discrete Data, lossless Recover
• The RpclbH(Z)H(YY), In this case, when either
  channel noise or the accumulated drift is small,
  the cost of correct errors is not take too many
  bits, however, if they are big, the rate penalty
  is significant.
• Jiontly Gaussian Data, Recovery with MSEltD
• In general, if the channel noise is too big, this
  system is akin to the case of not sending the
  block at all.

14
A Theory for Distributed Video Coding

• Complexity Performance Trade-Offs
• Typically, the more the complexity invested in
  the motion estimation process, the more accurate
  is the estimate of the statistics leading to
  better compression performance.

15
PRISM Encoding

• Decorrelating Transform (DCT on source block)
• Quantization
• Classification
• Syndrome Encoding
• Hash Generation

16
PRISM Encoding

• Classification

Figure 5 A bit plane view of a block of 64
coefficients. Bit planes are arranged in
increasing order with 0 corresponding to
the least-significant bit.
17
Classification

• depending on the available complexity budget, as
  well as the prevailing channel conditions, the
  classification module can perform varying degrees
  of motion search, ranging from an exhaustive
  motion search to a coarse motion search to no
  motion search at all.

18
PRISM Encoding

• Hash Generation
• A hash signature for the quantized sequence
  codewords is more pratical to let decoder know
  which is the best predictor for the block X.

19
PRISM Encoding
Figure 6 Bit stream associated with a block.
Figure 7 Functional block diagram of the encoder.
20
PRISM Decoding
Figure 8 Functional block diagram of the decoder.
21
Simulation Results
Figure 9 encoding rate comparison
22
Simulation Results
Figure 10 packet drop rate comparison
23
Simulation Results
Figure 11 frame Number comparison
24
Summary

• The PRISM is a pratical video coding framework
  built on distributed source coding principles.
  Base on a generalization of the classical
  Wyner-Ziv step, PRISM is characterized by
  inherent system uncertain about the state of
  the relevant side information that is know at the
  decoder. The two main architectural goals of
  PRISM make it radically different from existing
  video codecs.