A  -domain Rate Controller for Multiplexed Video Sequences

1. A -domain Rate Controller for Multiplexed Video Sequences G. Valenzise*, M. Tagliasacchi*, S. Tubaro*, L. Piccarreta *Dipartimento di Elettronica e Informazione, Politecnico di Milano Picture Coding Symposium 2007 November 7-9, 2007 – Lisboa, Portugal

2. Multiplexing of video sequences • Transmitmultiple video streamsover a sharedchannel • Broadcast television • Video-surveillance • etc… • The channelbandwidthislimited • Equalbandwidthpartitioningisnotoptimal

3. Optimal multiplexing quality quality time MINAVE Minimize the output averagedistortion MINVAR Minimize the output distortionvariance time quality time • Findanoptimal way to allocate channelbandwidthamongsequences • Example: two video sequences

4. Agenda • Formulate the MINAVE and MINVAR problems in the -domain • Assumptions: • Constant bit rate (CBR) channel • Frame-by-frameoptimization • Find a closedformsolutionfor the MINVAR • Compare the MINAVE and MINVAR criteria • Check the codingefficiency loss for the averagedistortion • Relax the CBR assumption • Temporalsmoothing

5. Problem formulation Rate-distortion operational curve of each frame can be described in the ρ-domain (He and Mitra, 2002): ρ-domain parameters can be estimated from decoded sequences

6. Problem formulation - MINAVE (He and Mitra, 2002)

7. Problem formulation - MINVAR Which is equivalent to solving When

8. MINAVE vs. MINVAR (simulation) MINAVE MINVAR

9. MINAVE vs. MINVAR • AveragedistortionofMINAVE • AveragedistortionofMINVAR • Weknow (bydefinition!) • QUESTION: • Whatis the codingefficiencyloss?

10. MINAVE vs. MINVAR: averagedistortionsurface MINVAR (suboptimal) Global Optimum (MINAVE)

11. CodingEfficiency Loss • Averagedistortionof MINAVE • Averagedistortionof MINVAR • The codingefficiency loss is

12. Simulations: CodingEfficiency Loss

13. TemporalSmoothing • Relax the CBR assumption • Introduce a shared encoder buffer toperform VBR encoding • Weapply the MINVAR rate allocationwhile at the sametimeachievingtemporalsmoothing • Foreachtimeinstant: • Compute the CBR distortionprofile • Smoothitwith the low-passfilter (He, Zen and Chen, 2005) • Set Dsmoothas the target distortion and computeratesRi • Relax or tighten the rate constraintaccordingto the current buffer level

14. Temporal smoothness

15. Experiment: transcoding Rate controller H.264 bitstream H.264 decoder H.264 encoder BUFFER H.264 decoder H.264 encoder H.264 bitstream ... H.264 decoder H.264 encoder H.264 bitstream

16. H.264/AVC results MINAVE MINVAR smoothed MINVAR

17. H.264/AVC results MINAVE MINVAR smoothedMINVAR

18. Conclusions • Summary: • Proposed a MINVAR bit allocationformultiplexed video sequences • The MINVAR allocationleverages on the -domain model (butworks on anyexponentialmodel, i.e. at high rates) • The codingefficiency loss w.r.t. MINAVE is, on average, of 0.5 dB • Future work: • Apply the MINVAR approachtoScalable Video Coding solve a discreteoptimizationproblem…

19. Thankyou! Questions?