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Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li...

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Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for video technology, 2009
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Page 1: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Compressed-domain-based Transmission Distortion Modeling for

Precoded H.264/AVC Video

Fan liGuizhong Liu

IEEE transactions on circuits and systems for video technology, 2009

Page 2: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Outline

Introduction Transmission Distortion Modeling Experimental result and discussion Accuracy and Complexity analysis Example Conclusion

Page 3: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Introduction

When the video sender drops packets due to congestion, or when packets are lost in the channel, transmission error occurs and would further propagate to its subsequent frames along the motion prediction path.

Traditional methods, such as ROPE, are pixel domain based distortion estimation, which are computationally inefficient.

Page 4: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Transmission Distortion Modeling

Since the decoding resynchronization is done at the slice header for the H.264 video, the loss of any packet in one slice will cause unsuccessful decoding of the whole slice. Thus the transmission distortion caused by the transmission errors can be calculated as follows:

From the expected loss probability of the slice

Assumed a simple error concealment strategy Temporal Replacement (TR) by copying the information of the entire slice at the corresponding location of the latest decoded frame.

Page 5: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Transmission Distortion Modeling

Estimation of DL(f,n)

(f, n, i) and (f, n, i) be the ith reconstructed pixel of the nth slice in the fth frame at the encoder and decoder

F̂ F~

f-1 f

ff-1

A

Bf-1

Page 6: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Transmission Distortion Modeling

Estimation of RFD(f, f -1, n)

Qi,j represents the relative motion intensity of the jth block in the ith inter-coded MB

Page 7: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Transmission Distortion Modeling

Estimation of DR(f,n)

MB is intra-coded

Page 8: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Transmission Distortion Modeling

MB is inter-coded

Page 9: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Experimental result and discussion

Selection of WiThe relative value of the distortion is estimated by the CDB model. Therefore, we only focused on the proportion between Wi of the intercoded prediction to that of the intra-coded prediction for both the 16*16 and 4*4 modes. Compare Wi = (β, 1.1β, 1.2β), (β, 1.2β, 1.4β), (β, 1.3β, 1.5β), and (β, 1.4β, 1.6β)

Page 10: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Experimental result and discussion

V2(Wi = (β, 1.2β, 1.4β)) fits best with the actual RFD and smallest deviation

Page 11: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Experimental result and discussion

Estimation of transmission distortion at PER=10%

Estimation of time-varying channel (wireless network)

Page 12: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Experimental result and discussion

influence of the bit rate to the accuracy of the CDB model

Average Error Rate

Page 13: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Experimental result and discussion

Page 14: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Experimental result and discussion

Complexity Analysis Feature extraction

Experiment results show that the processing time of the CDB model is only 42.8% of that in the ROPE and LPP approaches.

Distortion estimation CDB model is based on the MB level estimation.

On the contrary, the ROPE and LPP approaches are based on the pixel level estimation, and computation is operated per pixel. Number of operations in the CDB model is approximately 1.34%-1.75% of the number in the ROPE and LPP approaches.

Page 15: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Example

A base station delivers the video streams to three mobile users and uses TDMA based scheduling…

Page 16: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Example

Decision function

Object function

Page 17: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Example

CLD : using the LPP model as the decision function

CDBRA scheme outperforms the CLD scheme by 1.46 dB, and the no optimization scheme by 2.82 dB.

Page 18: Compressed-domain-based Transmission Distortion Modeling for Precoded H.264/AVC Video Fan li Guizhong Liu IEEE transactions on circuits and systems for.

Conclusion

A compressed domain approach to the transmission distortion modeling has been proposed. The approach has a much lower computational complexity when compared with that in the conventional pixel-domain-based methods and also provide fine accuracy and robustness.


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