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Rate-distortion Optimized Mode Selection Based on Multi-channel Realizations. Markus G ärtner Davide Bertozzi Classroom Presentation 13 th March 2001. Overview. Hybrid Video Coding Proposed Architecture Multi-channel realizations Performance Measurements: Concealment Techniques

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rate distortion optimized mode selection based on multi channel realizations

Rate-distortion Optimized Mode Selection Based on Multi-channel Realizations

Markus Gärtner

Davide Bertozzi

Classroom Presentation

13th March 2001

overview
Overview
  • Hybrid Video Coding
  • Proposed Architecture
  • Multi-channel realizations
  • Performance Measurements:
    • Concealment Techniques
    • Number of Channel Realization
    • Error Propagation
  • Conclusions

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

motion compensated hybrid coder
Motion-compensated hybrid coder

Mode Control

Encoder

XOR

Decoder

Intraframe DCT coder

IntraframeDecoder

Motion compensated predictor

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

proposed improvements over h 263
Proposed Improvements over H.263
  • H.263 Hybrid Video Coder:
    • Error propagation in the decoder loop neglected
    • Error-free transmission assumed
    • Threshold based mode selection
  • Goals of our approach:
    • Simulation of several channel conditions
    • Prediction of the error incurred at the receiver
    • Rate-Distortion optimized mode selection

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

multiple channel realizations
Multiple Channel Realizations

output

Coder

Frame Buffer

Decoder

OriginalEncoder

nth Channel Realization

input

Inter

Channel n

Decoder

Conceal-ment & Mode Decision

Intra

Channel n

Decoder

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

channel realizations
Channel Realizations
  • Randomly generated error patterns for each channel
  • Capture different sensitivity of macro-blocks to errors

X

Channel 1

X

Channel 2

X

Estimate of the real channel conditions (on the average)

Channel n

X

X

Group of blocks (GOB)

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

error concealment
Error Concealment

X

X

X

X

X

X

  • Bit error causes loss of macro block
  • Synchronization markers before each GOB
    • Macro block concealment
    • GOB concealment
    • Concealment of rest of GOB

Erroneous macro-blocks are replaced by respective macro-block of previously reconstructed frame

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

distortion measure
Distortion Measure

For each Macro-block:

Channel 1

Channel N

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

mode selection
Mode Selection

>

<

Mode Selection

Input Frame

  • Decision takes place for each macro-block  selection table
  • Computational complexity

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

channel decoder
Channel Decoder

Intra: quantized frame

  • Inter: previous frame buffer content + difference signal
  • Intra: quantized frame

input

Coder

Inter: difference signal, motion vectors

Foreachchannel:

Mode

Selection table

Reconstructed Frame

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

experimental setup
Experimental Setup

Rate

Distortion

Quantizer

Encoder

Frame Buffer

Channel

Decoder

Dequantizer

Frame Buffer

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

performance measurement i
Performance Measurement (I)

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

performance measurement ii
Performance Measurement (II)

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

number of realizations
Number of Realizations

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

error propagation i
Error Propagation (I)
  • First I-Frame received in error

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

error propagation ii
Error Propagation (II)
  • First I-Frame received correctly

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001

conclusions
Conclusions
  • Suitability for error-prone environments
    • Better performance than H.263
    • Reduction of error propagation
  • Limitations
    • Advanced modes of H.263 not considered
    • Computational complexity
  • Application for downloadable multimedia
  • Future work:
    • Sophisticated channel models
    • Implementation of advanced features

Markus Gärtner, Davide Bertozzi: Robust Video coding

Stanford University, 13th March 2001