dvc bitstream reorganiser for mobile devices

DVC bitstream reorganiser for mobile devices

C.K. Kim , D.Y. Suh, J. Park , B. Jeon

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DVC

bitstream reorganiser

Mobile-to-mobile video communications require both an encoder and a decoder to have low complexity.

High complexity at the DVC decoder side makes it difficult for resource-constrained mobile devices to perform decoding.

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DVC bitstream reorganiser estimates block-wise motion vectors and sends the motion information and the parity data required for decoding to the decoder

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DVC encoder (block A) DVC bitstream reorganiser (block B) DVC decoder (block C)

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Conventional DVC decoder Parity amount estimator Side information renovator

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Bitstream reorganiser

Side information renovator(ME) Parity amount estimator

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Block B

Generates side information using decoded KEY and WZ pictures.

The decoded WZ pictures exploited here to generate side information enhance the quality of that information.

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Side information renovator

A precise estimation of the parity data required for decoding is possible after Slepian-Wolf decoding has been performed.

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parity amount estimator

Eventually, the estimated amount of parity bits and motion information obtained in the generation of side information are delivered to the DVC decoder at the target device.

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Block B (cont.)

The WZ picture decoder (block C 2 ) decoding is faster.

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Block C

This is because the decoded KEY pictures and motion information passed from the DVC bitstream reorganiser (block B) enable it to generate the side information without performing motion estimation.

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Block C(cont.)

Increasing the decoding speed The side information generated at the DVC

decoder (block C) is as good as the information generated in the side information renovator (block B 3 ) in terms of Quality

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Block C(cont.)

The amount of parity bits required for Slepian-Wolf decoding is fed into the WZ picture decoder (block C 2 ) at this time.

The removal of iterative channel decoding contributes to reducing computational cost.

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Block C(cont.)

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Simulation results

DVC bitstream reorganiser which reduces decoder complexity so that decoder speed becomes 10 to 25times faster.

The DVC bitstream reorganiser sends the motion information and parity bits required for DVC decoding to the decoder at the target device.

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Conclusion

Mobile to Mobile Video Communication using DVC Framework with Channel Information Transmission

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Survey

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Heavy DVC decoding complexity

However it can have additional quality degradation coming from re-quantization

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DVC to H.264 Trans-coding Approach

However, as motion vector information and parity length information increases, its RD performance can be degraded.

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DVC bit-stream reorganization with motion vector

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Proposed Scheme

CNM1 estimates the Laplace distribution parameter for each block◦ It only uses already decoded key pictures

CNM2 also uses decoded Wyner-Ziv picture information◦ globally estimate it. Therefore, performance by

CNM2 is limited we selectively use CNM1 and CNM2 by

considering the bit rate.

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Correlation Noise Modeling(CNM)

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EXPERIMENT RESULTS

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DVC decoding complexity

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9/14->10/14 ◦ mobile to PC

10/14->11/14◦ Mobile to mobile

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Schedule

Thank you

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The end