A Robust Resolution-Enhancement Scheme for Video Transmission

Document Sample
A Robust Resolution-Enhancement Scheme for Video Transmission Powered By Docstoc
					 A Robust Resolution-Enhancement
Scheme for Video Transmission Over
     Mobile Ad-Hoc Networks

 Authors :
 Source :IEEE TRANSACTIONS ON
 BROADCASTING,         VOL. 54, NO. 2, JUNE
 2008
 Speaker :廖麗雅
 Adviser :林國祥
   12/30/2013                                 1
      Outline
n   INTRODUCTION
n   PRELIMINARIES
n   ADAPTIVE ERROR-RESILIENT STRATEGY
n   ROBUST SUPER-RESOLUTION ALGORITHM
n   SIMULATION RESULTS AND DISCUSSIONS
n   CONCLUSIONS AND FUTURE WORK


      12/30/2013                         2
        INTRODUCTION
n   mobile ad-hoc networks (MANETs)
n   Error-prone network
    n   may result in packet loss
n   solve the following primary technical challenges:
     n Trade-off between coding efficiency and error

       resilience
         n   MPEG - 2 / 4和H.263 / 4
               n   Error propagation
         n   Error resilience
        12/30/2013                                      3
        INTRODUCTION
    n   Enhance resolution under the scenario of packet
        loss
         n   super resolution (SR)
n   necessary to differentiate error concealment
    (EC) with SR
    n   provides relatively efficient compression and
        transport performance
    n   provides robust resolution-enhancement
        performance in the presence of various packet
        loss rates
        12/30/2013                                        4
      Outline
n   INTRODUCTION
n   PRELIMINARIES
n   ADAPTIVE ERROR-RESILIENT STRATEGY
n   ROBUST SUPER-RESOLUTION ALGORITHM
n   SIMULATION RESULTS AND DISCUSSIONS
n   CONCLUSIONS AND FUTURE WORK


      12/30/2013                         5
         PRELIMINARIES
n   overview system framework of the video
    transmission and processing
    n   present some related technical preliminaries
         n   Shifted 3-D SPIHT algorithm
         n   multiple description coding




         12/30/2013                                    6
        System Overview
n   The total architecture of video transmission
    and processing
    n   composed of three processes
         n   Image degradation
         n   Image transmission over error-prone networks
         n   Image SR reconstruction process




        12/30/2013                                          7
  System Overview




Fig. 1. The total architecture of video transmission and processing.
  12/30/2013                                                           8
       Shifted 3-D SPIHT Algorithm
n   rate-distortion performance
n   groups of wavelet transform coefficients
n   helpful to reduce the error propagation
n   How coefficients in a 3-D transform are
    related according to their spatial and
    temporal domains


       12/30/2013                              9
      Shifted 3-D SPIHT Algorithm
n   The essential aim is the wavelet coefficients
    from different sub-bands are interleaved to
    form independent packets that can be
    decoded independently




       12/30/2013                                   10
Shifted 3-D SPIHT Algorithm




 Fig. 2. Structure of the spatiotemporal relation of 3-D SPIHT.
 (a)Traditional 3-D SPIHT.
 (b)(b) Shifted 3-D SPIHT.
12/30/2013                                                        11
         Multiple Description Coding
n   As to the way to protect data from packet
    losses induced by the error-prone channels
    n   Add the redundant information at the bitstream
n   The fundamental principle of MDC
    n   generate multiple correlated descriptions of the
        source
n   The benefits of using MDC
    n   combined with path diversity (PD)
         12/30/2013                                        12
      Outline
n   INTRODUCTION
n   PRELIMINARIES
n   ADAPTIVE ERROR-RESILIENT STRATEGY
n   ROBUST SUPER-RESOLUTION ALGORITHM
n   SIMULATION RESULTS AND DISCUSSIONS
n   CONCLUSIONS AND FUTURE WORK


      12/30/2013                         13
       ADAPTIVE ERROR-RESILIENT
       STRATEGY
n   a novel error-resilient strategy is proposed
    based on partitioning the GOF (group of
    frames) into variable substreams with
    different priority levels adapting to the
    current network condition.




       12/30/2013                                  14
       Unequal Error Protection
n   provide a natural basis for unequal error
    protection (UEP)
n   propose a novel UEP based on the expected
    lifetime




       12/30/2013                               15
        Unequal Error Protection
n   in order to realize the proposed UEP, we
    modify the traditional DSR (Dynamic Source
    Routing)
    n   adding the node’s ID to the request packet
    n   adds the information of transmit power
    n   remaining energy to the request packet



        12/30/2013                                   16
      Flexible MDC
n   give an oversimplified method to compute
    the minimum needed substream number
    according to the packet loss rate (PL)of the
    obtained channels

G:packets are received correctlyand timely
B:packets are assumed to be lost
p from state G to B
q from state B to G
      12/30/2013                                   17
        Flexible MDC
n   average length of burst errors LB



n   data distribution , contains two aspects:
    n   decision of the wavelet decomposition level
    n   data distribution among these determinate paths


        12/30/2013                                    18
        Flexible MDC
n   Three basic principles:
    n   equity principle
    n   Highest priority level
    n   As to other parts of the data , use the best-effort
        strategy to transmit




        12/30/2013                                       19
      Outline
n   INTRODUCTION
n   PRELIMINARIES
n   ADAPTIVE ERROR-RESILIENT STRATEGY
n   ROBUST SUPER-RESOLUTION ALGORITHM
n   SIMULATION RESULTS AND DISCUSSIONS
n   CONCLUSIONS AND FUTURE WORK


      12/30/2013                         20
      ROBUST SUPER-RESOLUTION
      ALGORITHM
n   propose a robust SR algorithm taking into
    consideration the various packet loss scenarios
    to enhance the resolution of received image
n   propose a simplified estimator to estimate the
    lost wavelet coefficients
n   A series of convex sets which extract the exact
    detail information hidden among the adjacent
    images are constructed by taking advantage of
    the correlation of the wavelet coefficients
       12/30/2013                                     21
       Simplified Estimator
n   propose a simplified estimator to estimate
    the lost coefficients
n   different strategies are employed to deal with
    the different kinds of packet loss
n   propose a low-complexity solution



       12/30/2013                                22
        Simplified Estimator
n   the wavelet decomposition, the sender bi-
    linearly interpolates each scaling coefficients
n   This process is done twice
    n   approximation is obtained by using a horizontal
        interpolation
    n   approximation by using a vertical interpolation



        12/30/2013                                        23
       Simplified Estimator
n   absolute differences (SAD) values for these
    two subbands compared to the original LLk
    subband: SADv and SADh



I :interpolated         Gh-v:direction
O: original
W: comparison region
       12/30/2013                                 24
        Simplified Estimator
n   define five classes:
    n   (a) strong horizontal correlation(Gh-v >A)
    n   (b) weak horizontal correlation(A>=Gh-v>B)
    n   (c) isotropic(B>=Gh-v>=-B)
    n   (d) weak vertical correlation(-B>Gh-v>=-A)
    n   (e) strong vertical correlation(-A > Gh-v)
A:15
B:5
        12/30/2013                                   25
  Simplified Estimator




Fig. 3. Labeling of the weights used in calculation at the missing sample.
 (a)Mask used in low-frequency subband.
 (b) Mask used in high-frequency subband.
  12/30/2013                                                                 26
Simplified Estimator




12/30/2013             27
      Simplified Estimator
n   label the weighting factors
n   horizontal neighbors are labeled H0 and H1
n   vertical neighbors V0 and V1
n    diagonal neighbors D0 ,D1 ,D2 , and D3.




      12/30/2013                                 28
      Simplified Estimator
n   weighting factors can be set




      12/30/2013                   29
        Projection Onto Convex Sets
n   a projection procedure is utilized to extract
    information hidden in a group of video
    frames to update the wavelet coefficients
n   The constructed convex set
    n   enhance the resolution of the received images
    n   reduce the artifacts generated during the
        projection process


        12/30/2013                                      30
     Projection Onto Convex Sets




horizontal, vertical and diagonal directions

translated coarse scaling function
     12/30/2013                                31
Projection Onto Convex Sets




12/30/2013                    32
Fig. 4. Flow chart of the proposed robust SR method.
     12/30/2013                                        33
      Outline
n   INTRODUCTION
n   PRELIMINARIES
n   ADAPTIVE ERROR-RESILIENT STRATEGY
n   ROBUST SUPER-RESOLUTION ALGORITHM
n   SIMULATION RESULTS AND DISCUSSIONS
n   CONCLUSIONS AND FUTURE WORK


      12/30/2013                         34
     SIMULATION RESULTS AND
     DISCUSSIONS
n   First of all , we describe the simulation
    environment
n   Secondly, we present the main simulation
    results where we show the objective and
    subjective results of the performance of the
    proposed system under different scenarios
n   Finally, we conclude this section by
    summarizing the conclusions to be drawn based
    on the selected simulation results described
      12/30/2013                                35
       Simulation Environment
n   The two standard video sequences , Foreman
    and Weather forecast , are encoded with shifted
    3-D SPIHT algorithm
n   In order for objective comparison, PSNR at the
    receiver relative to the original HR video
    sequence is used and its definition is
              PSNR(dB) = 10log10(2552 / MSE)
n   MSE is the mean-square error between the
    original the reconstructed luminance frame
       12/30/2013                                 36
     Simulation Environment




Fig. 5. Performance achieved by proposed method for the Foreman sequence,
at the rb = 96Kbps and LB = 4.
     12/30/2013                                                             37
   Simulation Environment




Fig. 6. Performance achieved by proposed method for the Foreman sequence,
at the rb = 256 Kbps and LB = 4.
   12/30/2013                                                           38
           Simulation Environment




Fig. 7. Performance achieved by proposed    Fig. 8. Performance achieved by proposed
method for the Weather forecast             method for the Weather forecast
sequence, at the rb = 96 Kbps and LB = 4.   sequence, at the rb = 256 Kbps and LB =
                                            4.
           12/30/2013                                                            39
Fig. 9. Subjective results achieved by proposed method and other comparison schemes,
for the Weather forecast at rb = 256Kbps, LB = 4 and PL = 15%:
(a) bilinear method; (b) fixed method; (c) unbalanced method; (d) proposed method.
           12/30/2013                                                            40
       Observations
n   The adaptive error-resilient strategy has played
    an important role in the whole video
    transmission system
n   The proposed SR algorithm actually can
    enhance the resolution of the received image
n   No matter the video sequence is high-motion or
    low-motion, the packet loss rate is high or low,
    the proposed method can perform well all the
    time
       12/30/2013                                  41
      Outline
n   INTRODUCTION
n   PRELIMINARIES
n   ADAPTIVE ERROR-RESILIENT STRATEGY
n   ROBUST SUPER-RESOLUTION ALGORITHM
n   SIMULATION RESULTS AND DISCUSSIONS
n   CONCLUSIONS AND FUTURE WORK


      12/30/2013                         42
       CONCLUSIONS AND FUTURE
       WORK
n   We propose a robust resolution-enhancement
    scheme for video stream transmission over
    mobile ad-hoc networks
n   The SR algorithm performs well in presence of
    different kinds of packet loss rates
n   Our future work is to reduce its complexity to
    adapt to the real-time wireless video
    transmission

       12/30/2013                                    43
             The End

12/30/2013             44

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:0
posted:12/30/2013
language:Unknown
pages:44