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Scalable Video Conferencing Using Subband Transform Coding and Layered Multicast Transmission

Scalable Video Conferencing Using Subband Transform Coding and Layered Multicast Transmission. Mathias Johanson Swedish Research Institute for Information Technology mathias@siti.se. Scalability in Videoconferencing. Large number of video receivers (and senders)

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Scalable Video Conferencing Using Subband Transform Coding and Layered Multicast Transmission

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  1. Scalable Video ConferencingUsing Subband Transform Coding and Layered Multicast Transmission Mathias Johanson Swedish Research Institute for Information Technology mathias@siti.se

  2. Scalability in Videoconferencing • Large number of video receivers (and senders) • Multiple quality levels in a single multipoint conference session • Differentiated host and network requirements • Realizable over public internetworks

  3. Limitations of Traditional Videoconferencing Systems • CODEC operates at fixed bandwidth • Multipoint operation involves gateways • Differentiated quality levels in a multipoint session require transcoders that are expensive and introduce latency • Often dependent on level 2 network protocols (e.g. ISDN systems)

  4. Approach... • Scalable codec based on subband transform coding • Receiver-driven layered IP-multicast transmission • Software implementation + DSP-based implementation

  5. Layered Video Coding • Temporal layering • Increased number of refinement layers correspond to higher framerate • Spatial layering • Increased number of refinement layers correspond to higher image resolution • Layered quantization • Increased number of refinement layers correspond to finer quantization

  6. Channel 4 Channel 3 Channel 2 Channel 1 Temporal Layering Images of a video sequence Transmission channels that can be received independently

  7. Channel 1 Channel 3 Channel 2 Spatial Layering Transform Base signal + refinement signals Original image

  8. Layered image and video encoding/compression formats • Hierarchical JPEG • MPEG-2 scalable mode • temporal, spatial, SNR scalability • H.263 scalable mode • Wavelets Block-based DCT Subband transform

  9. Spatial scalability in block based image and video encodings Base Encode layer Decode Down- sample Upsample x(t) Refinement Encode layer

  10. y (t) 0 2 x(t) y (t) 1 2 Wavelet-based approach to spatial scalability baselayer Encode G low refinementlayer Encode G high Quadrature mirror filters implementing the wavelet transform

  11. Wavelet transform Original image horizontal transform vertical transform Iterate…. Transformed image

  12. Colorspace conversion and subsampling RGB -> YCrCb 4:2:2 Wavelet transform (separately on Y, Cr, Cb) Subband decomposition Quantization of each subband/component Lossy compression step Huffman encoding entropy coding Wavelet compression

  13. Communication Architecture • Transmit the subbands of the transformed images on separate channels that can be received independently • Multicasting • Leaf-initiated JOIN-mechanism RLM Receiver-driven Layered (IP) Multicast

  14. 224.3.4.5 Base layer 224.3.4.6 224.3.4.7 Refinement layers 224.3.4.8 Multicast router Low bandwidth High bandwidth Internet R Receiver (1 layer) Sender Receiver (4 layers)

  15. Wavelet RTP header

  16. Prototype implementation • Based on Smile! • Software wavelet codec • Receiver-driven layered IP multicast network module • RTP/RTCP • Spatial and temporal scalability • SGI O2, MIPS R5000 processor

  17. Usage Scenario highly heterogeneous environment Internet Low quality Medium quality Dial-up access Leased Line Leased Line R High-speed LAN Transmitter High quality

  18. Performance Tests Image quality scalability Bandwidth scalability

  19. Future work... • Temporal compression • DSP implementation (TMS320C80 or similar) • Automatic selective refinement based on ”bandwidth discovery” • Subband audio coding

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