a robust resolution-enhancement scheme for video transmission over mobile ad-hoc networks authors :...

A Robust Resolution-Enhancement Scheme for Video

Transmission OverMobile Ad-Hoc Networks

Authors :Source :IEEE TRANSACTIONS ON BROADCASTING, VOL. 54, NO. 2, JUNE 2008Speaker :廖麗雅Adviser :林國祥

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Outline

INTRODUCTION PRELIMINARIES ADAPTIVE ERROR-RESILIENT STRATEGY ROBUST SUPER-RESOLUTION

ALGORITHM SIMULATION RESULTS AND

DISCUSSIONS CONCLUSIONS AND FUTURE WORK

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INTRODUCTION

mobile ad-hoc networks (MANETs) Error-prone network

may result in packet loss solve the following primary technical

challenges: Trade-off between coding efficiency and

error resilience MPEG - 2 / 4 和 H.263 / 4

Error propagation Error resilience

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Enhance resolution under the scenario of packet loss

super resolution (SR) necessary to differentiate error

concealment (EC) with SR provides relatively efficient compression

and transport performance provides robust resolution-enhancement

performance in the presence of various packet loss rates

INTRODUCTION

Outline




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PRELIMINARIES

overview system framework of the video transmission and processing present some related technical

preliminaries Shifted 3-D SPIHT algorithm multiple description coding

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System Overview

The total architecture of video transmission and processing composed of three processes

Image degradation Image transmission over error-prone networks Image SR reconstruction process

112/04/20 8Fig. 1. The total architecture of video transmission and processing.

System Overview

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Shifted 3-D SPIHT Algorithm

rate-distortion performance groups of wavelet transform coefficients helpful to reduce the error propagation How coefficients in a 3-D transform are

related according to their spatial and temporal domains

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The essential aim is the wavelet coefficients from different sub-bands are interleaved to form independent packets that can be decoded independently


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Fig. 2. Structure of the spatiotemporal relation of 3-D SPIHT. (a)Traditional 3-D SPIHT. (b)(b) Shifted 3-D SPIHT.


Multiple Description Coding

As to the way to protect data from packet losses induced by the error-prone channels Add the redundant information at the

bitstream The fundamental principle of MDC

generate multiple correlated descriptions of the source

The benefits of using MDC combined with path diversity (PD)

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Outline




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ADAPTIVE ERROR-RESILIENT STRATEGY

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.

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Unequal Error Protection

provide a natural basis for unequal error protection (UEP)

propose a novel UEP based on the expected lifetime

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in order to realize the proposed UEP, we modify the traditional DSR (Dynamic Source Routing) adding the node’s ID to the request packet adds the information of transmit power remaining energy to the request packet

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Unequal Error Protection

Flexible MDC

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 timelyB:packets are assumed to be lostp from state G to Bq from state B to G

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average length of burst errors LB

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

paths112/04/20 18

Flexible MDC

Three basic principles: equity principle Highest priority level As to other parts of the data , use the best-

effort strategy to transmit

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Flexible MDC

Outline




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ROBUST SUPER-RESOLUTION ALGORITHM

propose a robust SR algorithm taking into consideration the various packet loss scenarios to enhance the resolution of received image

propose a simplified estimator to estimate the lost wavelet coefficients

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

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Simplified Estimator

propose a simplified estimator to estimate the lost coefficients

different strategies are employed to deal with the different kinds of packet loss

propose a low-complexity solution

the wavelet decomposition, the sender bi-linearly interpolates each scaling coefficients

This process is done twice approximation is obtained by using a

horizontal interpolation approximation by using a vertical

interpolation

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absolute differences (SAD) values for these two subbands compared to the original LLk subband: SADv and SADh

I :interpolated Gh-v:direction

O: originalW: comparison region

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define five classes: (a) strong horizontal correlation(Gh-v >A) (b) weak horizontal correlation(A>=Gh-v>B) (c) isotropic(B>=Gh-v>=-B) (d) weak vertical correlation(-B>Gh-v>=-A) (e) strong vertical correlation(-A > Gh-v)

A:15B:5

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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.


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label the weighting factors horizontal neighbors are labeled H0

and H1 vertical neighbors V0 and V1 diagonal neighbors D0 ,D1 ,D2 , and

D3.

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weighting factors can be set

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Projection Onto Convex Sets

a projection procedure is utilized to extract information hidden in a group of video frames to update the wavelet coefficients

The constructed convex set enhance the resolution of the received

images reduce the artifacts generated during the

projection process112/04/20 30

horizontal, vertical and diagonal directions

translated coarse scaling function112/04/20 31


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Fig. 4. Flow chart of the proposed robust SR method.

Outline




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SIMULATION RESULTS AND DISCUSSIONS

First of all , we describe the simulation environment

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

Finally, we conclude this section by summarizing the conclusions to be drawn based on the selected simulation results described

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Simulation Environment

The two standard video sequences , Foreman and Weather forecast , are encoded with shifted 3-D SPIHT algorithm

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) MSE is the mean-square error between the

original the reconstructed luminance frame112/04/20 36


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Fig. 5. Performance achieved by proposed method for the Foreman sequence,at the rb = 96Kbps and LB = 4.

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Fig. 6. Performance achieved by proposed method for the Foreman sequence,at the rb = 256 Kbps and LB = 4.


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Fig. 7. Performance achieved by proposed method for the Weather forecastsequence, at the rb = 96 Kbps and LB = 4.

Fig. 8. Performance achieved by proposed method for the Weather forecastsequence, at the rb = 256 Kbps and LB = 4.


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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.

Observations The adaptive error-resilient strategy has

played an important role in the whole video transmission system

The proposed SR algorithm actually can enhance the resolution of the received image

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

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Outline




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CONCLUSIONS AND FUTURE WORK

We propose a robust resolution-enhancement scheme for video stream transmission over mobile ad-hoc networks

The SR algorithm performs well in presence of different kinds of packet loss rates

Our future work is to reduce its complexity to adapt to the real-time wireless video transmission

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The End

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a robust resolution-enhancement scheme for video transmission over mobile ad-hoc networks authors :...

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