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Wyner-Ziv Video Coding With Improved 
Motion Field Using Bicubic Interpolation 
I Made Oka Widyantara 
Telecomunication System Lab. 
Department of Electrical Engineering 
Udayana University
Outline 
 Introduction 
 Proposed Wyner-Ziv Video codec 
 Bicubic Interpolation of motion field 
 Experiments and Results 
 Analysis of RD performance 
 Analysis of decosing complexity 
 Conclusions
Introduction 
 WZVC is the recent video coding paradigm based on 
the Slepian-Wolf, and Wyner-Ziv theorems which 
exploits the source temporal correlation at the 
decoder and not at the encoder. 
 The main problem in designing WZVC codec is a 
method of generating the SI at the decoder
Introduction 
 Motion vector learning based on Expectation Maximization 
(EM) algorithm is a method of generating SI for WZVC 
iteratively (Varodayan et.al., 2008). 
Rate control 
X S θ 
LDPC 
Encoder 
LDPC Dedoder 
(M-Step) 
ψ 
Probability 
Model 
Reconstruction 
^ 
X 
Block-based 
motion estimator 
(E-step) 
Ŷ 
Motion field 
interpolation 
P{Mi,j} P{Mu,v} 
 Motion field interpolation : refines the block based motion 
field P{Mu,v}to pixel precision P{Mi,j}, to improve the 
accuracy of the soft SI. 
 We proposed bicubic interpolation techniques, and make 
performance analysis WZVC codec, when compared with 
the implementation of bilinear interpolation technique 
(WZVC existing)
Proposed WZVC codec 
 Initialize block-based motion field :  
  
 
 
if M 
, (0,0) 
3 
3 
P M if M 
u v 
u v 
    
80 , 
   
 
 
otherwise 
u v 
t 
app 
, 
(0, ), ( ,0) 
2 
1 
80 
1 
4 
, 
2 
4 
, 
( )
Bicubic Interpolation of motion 
field 
 Uses sixteen probability distribution Papp{Mu,V(xS,yS)} that close to 
(xS,yS) position in block based motion field. 
 First, for each ysk, the algorithm determines four polynomial cubic 
F0(x), F1(x), F2(x), and F3(x) using: 
Fk(x) = akx3 + bkx2 + ckx + dk, ; 0 ≤ k ≤ 3 
such that : Fk(xS0) = Papp{Mu,v(xSo,ySk)}, Fk(xS1) = Papp{Mu,v(xS1,ySk)}, 
Fk(xS2) = Papp{Mu,v(xS2,ySk)}, Fk(xS3) = Papp{Mu,v(xS3,ySk)} 
 Then, the algorithm determines a cubic polynomial Fy(y) such that: 
Fy(yS0) = F0(xS), Fy(yS1) = F1(xS), Fy(yS2) = F2(xS), Fy(yS3) = 
F3(xS) 
 Finally, the value of probability distribution Papp{Mi,j(xD,yD)} is set on 
Fy(yS). 
Probability 
F0(x) 
F1(x) 
F2(x) F3(x) 
x 
y 
Papp{Mi,j(xS,yS)} 
xS 
xS3 
yS0 yS1 yS yS2 yS3 
xS0 
xS1 
xS2
Analysis of RD performance 
RD curves for GOP sizes 2, Foreman (left), Carphone (right) 
 WZVC codec with Bicubic interpolation produces an almost 
identical RD performance with existing WZVC codec with 
Bilinear interpolation. 
 At fixed rate, both interpolation techniques produce the same 
PSNR gain and constant throughout scaling factor quantization, 
Qf = 0.5, 1, 2 and 4. 
 Identical RD performance produced by both methods showed 
that Bicubic interpolation is able to produce a linear convex 
combination of probability on the interval [0,1].
Analysis of decoding complexity 
Foreman 
Carphon 
e 
 The decoding complexity is evaluated by measuring the average 
decoding time per quadrant of EM iteration time needed by 
decoder to fulfill the conditions of syndrome. 
 In general, for both video sequences used, the implementation of 
Bicubic interpolation reduces the complexity of the decoder 
WZVC 
 The most decrease in complexity occurred in scaling factor Qf = 
0.5 up to 9.49% for Foreman, and up to 7.33% for Carphone. 
This indicates that the codec WZVC with Bicubic interpolation is 
suitable to encode video sequences with high and complex 
motion content.
Conclusions 
 The new WZVC codec improves motion field 
probability distribution into pixel precision, using 
Bicubic interpolation technique. 
 Experimental results showed that implementation 
of bicubic interpolation technique reduces 
decoder complexity significantly with RD quality 
almost equal to previous learning based WZVC 
codec that use Bilinear interpolation.
Thank You

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Icici bme 2011

  • 1. Wyner-Ziv Video Coding With Improved Motion Field Using Bicubic Interpolation I Made Oka Widyantara Telecomunication System Lab. Department of Electrical Engineering Udayana University
  • 2. Outline  Introduction  Proposed Wyner-Ziv Video codec  Bicubic Interpolation of motion field  Experiments and Results  Analysis of RD performance  Analysis of decosing complexity  Conclusions
  • 3. Introduction  WZVC is the recent video coding paradigm based on the Slepian-Wolf, and Wyner-Ziv theorems which exploits the source temporal correlation at the decoder and not at the encoder.  The main problem in designing WZVC codec is a method of generating the SI at the decoder
  • 4. Introduction  Motion vector learning based on Expectation Maximization (EM) algorithm is a method of generating SI for WZVC iteratively (Varodayan et.al., 2008). Rate control X S θ LDPC Encoder LDPC Dedoder (M-Step) ψ Probability Model Reconstruction ^ X Block-based motion estimator (E-step) Ŷ Motion field interpolation P{Mi,j} P{Mu,v}  Motion field interpolation : refines the block based motion field P{Mu,v}to pixel precision P{Mi,j}, to improve the accuracy of the soft SI.  We proposed bicubic interpolation techniques, and make performance analysis WZVC codec, when compared with the implementation of bilinear interpolation technique (WZVC existing)
  • 5. Proposed WZVC codec  Initialize block-based motion field :      if M , (0,0) 3 3 P M if M u v u v     80 ,      otherwise u v t app , (0, ), ( ,0) 2 1 80 1 4 , 2 4 , ( )
  • 6. Bicubic Interpolation of motion field  Uses sixteen probability distribution Papp{Mu,V(xS,yS)} that close to (xS,yS) position in block based motion field.  First, for each ysk, the algorithm determines four polynomial cubic F0(x), F1(x), F2(x), and F3(x) using: Fk(x) = akx3 + bkx2 + ckx + dk, ; 0 ≤ k ≤ 3 such that : Fk(xS0) = Papp{Mu,v(xSo,ySk)}, Fk(xS1) = Papp{Mu,v(xS1,ySk)}, Fk(xS2) = Papp{Mu,v(xS2,ySk)}, Fk(xS3) = Papp{Mu,v(xS3,ySk)}  Then, the algorithm determines a cubic polynomial Fy(y) such that: Fy(yS0) = F0(xS), Fy(yS1) = F1(xS), Fy(yS2) = F2(xS), Fy(yS3) = F3(xS)  Finally, the value of probability distribution Papp{Mi,j(xD,yD)} is set on Fy(yS). Probability F0(x) F1(x) F2(x) F3(x) x y Papp{Mi,j(xS,yS)} xS xS3 yS0 yS1 yS yS2 yS3 xS0 xS1 xS2
  • 7. Analysis of RD performance RD curves for GOP sizes 2, Foreman (left), Carphone (right)  WZVC codec with Bicubic interpolation produces an almost identical RD performance with existing WZVC codec with Bilinear interpolation.  At fixed rate, both interpolation techniques produce the same PSNR gain and constant throughout scaling factor quantization, Qf = 0.5, 1, 2 and 4.  Identical RD performance produced by both methods showed that Bicubic interpolation is able to produce a linear convex combination of probability on the interval [0,1].
  • 8. Analysis of decoding complexity Foreman Carphon e  The decoding complexity is evaluated by measuring the average decoding time per quadrant of EM iteration time needed by decoder to fulfill the conditions of syndrome.  In general, for both video sequences used, the implementation of Bicubic interpolation reduces the complexity of the decoder WZVC  The most decrease in complexity occurred in scaling factor Qf = 0.5 up to 9.49% for Foreman, and up to 7.33% for Carphone. This indicates that the codec WZVC with Bicubic interpolation is suitable to encode video sequences with high and complex motion content.
  • 9. Conclusions  The new WZVC codec improves motion field probability distribution into pixel precision, using Bicubic interpolation technique.  Experimental results showed that implementation of bicubic interpolation technique reduces decoder complexity significantly with RD quality almost equal to previous learning based WZVC codec that use Bilinear interpolation.