DWT based Scalable video coding with scalable motion coding

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DWT based Scalable video coding with scalable
motion coding

• Syed Jawwad Bukhari

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Abstract

• The purpose of this project is to get
  understanding of DWT based scalable video
  compression.
• For wider variety of bit rates we need wide range
  scalability and hence the motion information must
  also be presented in some scalable form to get
  such wide range scalability.
• This project is based on study of different DWT
  based video compression techniques.
• Implementation of a Motion compensated
  Jpeg2000-like video coder.
• Review of scalable motion paper 1 is also
  presented.

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Introduction

• Video Compression
• Video compression methods use signal processing
  as well as video processing techniques for
  achieving maximum compression with in acceptable
  quality range.
• Trade off Perceptual Quality vs. Compression
  ratio.

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Scalable Video Compression

• Heterogeneous network users request for different
  type of quality for the same video
• E.g.
• a user with a lower bandwidth connection may
  require a low quality video
• a user watching the same video on a HDTV will
  require a video with much higher quality
  resulting in greater requirements for bandwidth.
• A mobile user will require the same video in a
  lower resolution mode due to smaller screen size
  and memory requirements.
• gt generic video coder to fulfill requirements
  for such a wide range of bit rates and qualities
• scalable video coding.

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Scalability

• Spatial scalability
• Temporal scalability
• SNR Scalability
• Data partition.
• ? Motion information should also be scalable for
  wide range of bit rates to be covered.

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DWT based scalable video coding

• DWT is widely used for scalable video coding.
• various approaches involving DWT to achieve
  scalable video coding
• 3D DWT, Temporal Filtering Motion prediction
• In this project
• Motion estimation on GOP (group of pictures)
  followed by 2D-DWT. (IMPLEMENTATION)
• EZW (REVIEW)

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JPEG2K like MC video coder
Image adapted from 5
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EZW (Embedded Zero-tree Wavelet)

• Shapiro presented the EZW algorithm in 4.

1 2 5 8 17 24 25 32
3 4 6 7 18 23 26 31
9 10 13 14 19 22 27 30
12 11 15 16 20 21 28 29
33 34 35 36 49 50 54 55
40 39 38 37 51 53 56 61
41 42 43 44 52 57 60 62
48 47 46 45 58 59 63 64
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5 step bit-plane coding in EZW

• Step 1 Set an initial threshold such that will
  only the first coefficient is greater than the
  threshold and no other is greater than the
  threshold.
• Step 2 Update the threshold to its half.

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5 step bit-plane coding in EZW

• Step 3 Significance pass. Scan insignificant
  values using baseline algorithm scan order as
  presented in the table above. Test each value if
  it greater than threshold then output the sign of
  value and set its quantized value to this
  threshold otherwise set the quantized value for
  this coefficient to zero.

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5 step bit-plane coding in EZW

• Step 4 Refinement pass. Scan significant values
  found with higher threshold values. For each
  significant value output a zero bit if it belongs
  to quantized value plus the threshold value
  interval otherwise output a one bit.
• Step 5 Repeat step 2 to 4.

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Scalable motion coding

• 1 claims that at lower resolutions motion
  compensation is lesser sensitive
• it requires lesser accuracy.
• According to 1 video is usually received at a
  lower resolution when transmission is over a
  lower bit rate channel. Its implication is that
  the motion vectors which were very accurate are
  almost useless as the smallest blocks vanish in
  lower resolutions.

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Implementations
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• Motion estimation algorithms were taken from 2,
  wavelet used and Huffman code for wavelet-based
  compression is also taken from 3.
• S-HAT is used as a metric for measuring quality.
  Its implementation is based on the details given
  in Tobagis paper.

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Parameters

• The parameters tested were
• motion vector block size,
• Search algorithm
• different setups of base and enhancements layers
  (spatial/ temporal/ data partition)
• Study of both scalable video coding as well as
  scalable motion coding.

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Results

• Seq Highway, B Sz 88, Resolution 256256

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Seq Highway, B Sz 88, Resolution 256256
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Seq Highway, B Sz 88, Resolution 128128
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Seq Highway, B Sz 88, Resolution 128128
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Seq Highway, B Sz 88, Resolution 128128
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Seq Highway, B Sz 88, Resolution 128128
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S-HAT Seq Highway
Series 1 256256, MB 88, Series 2 128128,
MB 44,
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Compression RatioSeq Highway
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References

1. Accuracy-scalable motion coding for efficient
   scalable video compression Boisson, Edouard
   Guillemot., 2004.
2. MATLAB File Exchange.
3. Digital Image Processing using MATLAB, Gonzalez,
   2004.
4. Embedded image coding using zero trees of
   wavelet coefficients. IEEE Trans. on Signal
   Processing, 41(12) 3445-3462, 1993.
5. The transform and data compression handbook