Rate-distortion Optimized Mode Selection Based on Multi-path Channel Simulation

Markus GärtnerDavide Bertozzi

Project ProposalClassroom Presentation

6th February 2001

Markus Gärtner, Davide Bertozzi: Robust Video codingStanford University, 6th February 2001

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Overview

Hybrid Video Coding

Mode selection

Previous works

Multi-path channel simulation:Architecture

Distortion Measure

Expected Results

Workplan

Markus Gärtner, Davide Bertozzi: Robust Video codingStanford University, 6th February 2001

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Motion-compensated hybrid coder

Intraframe DCT coder

Motion compensated

predictor

IntraframeDecoder

Mode Control

XOR

Decoder

Encoder

Markus Gärtner, Davide Bertozzi: Robust Video codingStanford University, 6th February 2001

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Inter- / Intra-frame coding

P Frame (inter): low bit rate, exploits temporal redundancysensitivity to error propagation

I Frame (intra): high bit rate, no temporal dependencystops error propagation

I Frame P Frame

Markus Gärtner, Davide Bertozzi: Robust Video codingStanford University, 6th February 2001

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Optimal Mode Selection

Salesman

Foreman

Packet error rate [%]

Intra [%]

2 4 6

10

20

30

Source: Färber, Stuhlmüller, Girod; ICIP 1999

Markus Gärtner, Davide Bertozzi: Robust Video codingStanford University, 6th February 2001

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Previous Approaches

Feedback based methodsTransmission delay limits applicability

Heuristic refresh frequency: periodic intra-coding of:

Whole frames (Turletti-Huitema)Random blocks (Coté-Kossentini)

Threshold methods (Liao-Villasenor, Färber-Steinbach-Girod)

Content adaptive methods (Haskell-Messerschmitt)

Rate-distortion optimization (Coté-Kossentini)

Markus Gärtner, Davide Bertozzi: Robust Video codingStanford University, 6th February 2001

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Block mode chosen according to

Error propagation only beyond one frame

Distortion measure as simple sum of Dq and Dc

Block-weighted Distortion Estimate

20

22

24

26

28

30

32

34

0 5 10 20

Packet Loss Rate

Y-P

SN

R R-D update

Random update

RpDDpJ cq )1(

Coté-Kossentini

Markus Gärtner, Davide Bertozzi: Robust Video codingStanford University, 6th February 2001

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Distortion is calculated for each pixel

Computational complexityHolds for inter-pel accuracy only

Recursive optimal per-pixel Estimate

MBi

iMB dD

SNRMiss

AmericaGrandma Salesman

Mother & Daughter

Carphone Foreman

ROPE 37.8 dB 35.4 dB 33.6 dB 32.8 dB 29.9 dB 26.7 dB

BWDE 37.2 dB 34.2 dB 31.6 dB 30.7 dB 28.1 dB 25.0 dB

Zhang-Reghunatan-Rose

Markus Gärtner, Davide Bertozzi: Robust Video codingStanford University, 6th February 2001

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Our Approach

Coder

Decoder Channel 1Distortion Estimate

Mode Selection

Decoder Channel 2

Decoder Channel n

Markus Gärtner, Davide Bertozzi: Robust Video codingStanford University, 6th February 2001

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H.263 Coding Standard

I-frame: DCT coding of each 8x8 blockP-frame: DPCM, 8x8 DCT coding of error, one motion vector per macroblockMode selection on macro-block basis

frame 16x16 macroblock 8x8 block

GOB

Markus Gärtner, Davide Bertozzi: Robust Video codingStanford University, 6th February 2001

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Channel Model

Model on macro-block basis

Channel 1

Channel 2

Channel n

X X

X

X

X

Group of blocks

“ControlledRandomness”

Markus Gärtner, Davide Bertozzi: Robust Video codingStanford University, 6th February 2001

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Distortion Measure

di comprises any distortion incurred by path i

)(min)(minmodemode

MBMBMB RDJ

),( TXqMB DDfD

R

D

N

iiiMB dw

ND

1

1

where

Our approach:

Markus Gärtner, Davide Bertozzi: Robust Video codingStanford University, 6th February 2001

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Expected Results

Channel modelling

Cote-Kossentini

H. 263

Average PSNR at decoder

Error probability

Markus Gärtner, Davide Bertozzi: Robust Video codingStanford University, 6th February 2001

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Workplan

Week 1 Week 2 Week 3 Week 4 Week 5

Literature Investigation

Setup of H.263

Implementation ofChannel models

Performance measurements

Final presentation