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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 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

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  1. Rate-distortion Optimized Mode Selection Based on Multi-channel Realizations Markus Gärtner Davide Bertozzi Classroom Presentation 13th March 2001

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. Distortion Measure For each Macro-block: Channel 1 Channel N Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13th March 2001

  9. 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

  10. 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

  11. 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

  12. Performance Measurement (I) Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13th March 2001

  13. Performance Measurement (II) Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13th March 2001

  14. Number of Realizations Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13th March 2001

  15. Error Propagation (I) • First I-Frame received in error Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13th March 2001

  16. Error Propagation (II) • First I-Frame received correctly Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13th March 2001

  17. 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

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