Two-Dimensional Channel Coding Scheme for MCTF- Based Scalable Video Coding IEEE TRANSACTIONS ON MULTIMEDIA,VOL. 9,NO. 1,JANUARY Yu Wang, Student Member, IEEE, Tao Fang, Member, IEEE, Lap-Pui Chau, Senior Member, IEEE, and Kim-Hui Yap, Member, IEEE csk 2007/03/20

Outline Introduction of UEP Introduction of MCTF Proposed 2D UEP scheme Genetic Algorithms Simulation and Performance Conclusion

Introduction of UEP Unequal error protection (UEP) is based on the priority encoding transmission (PET) It has been proven to be very promising to resolve this problem by taking advantage of the differential sensitivities of the output bit- streams of video encoder.

Introduction of MCTF Motion Compensated Temporal Filtering

Introduction of MCTF Motion Compensated Temporal Filtering  Wavelet base In temporal  Two frame (average, different) In PSNR  WT with EZW coding

Introduction of MCTF ． Reference: Overview on Scalable Video Coding - IIOverview on Scalable Video Coding - II

Introduction of MCTF WT with EZW coding

Introduction of MCTF

Proposed 2D UEP scheme

PSNR increment donated Probability of correctly receiving two-state Markov model approximates

Proposed 2D UEP scheme Channel bit-allocation matrix Constraint

Genetic Algorithms  Artificial mechanisms of natural evolution  A robust search procedures and solving complex search problems Disadvantage  Low efficient if large problem space  Population homogeneous

Genetic Algorithms End Begin Encoding Initialize population Reproduction & Selection Crossover Mutation Evaluate population Termination criterion Evaluate population No Yes Randomly produce and population size is kept constant Calculate the fitness by PSNR_overall To copy solution strings into a mating pool based on the fitness. Roulette wheel method is used Crossover probability Pc mutation probability Pm

Genetic Algorithms Roulette wheel method

Genetic Algorithms Sequence preserving crossover (SPX)  Schemata is preserved as more as possible. A=123||5748||69 B=934||5678||21 A’=234||5678||91 B’=936||5748|| (a) A (a) A ’ (a) B (a) B ’ Crossover

Point mutation Inversion mutation Shift mutation Genetic Algorithms (a) Point mutation (b) Inversion mutation (c) Shift mutation (right shift)

Simulation and Performance The number of generations: generations for all the test sequences l = 100, P c = 0.65, P m = 0.02 All programs were run on an Intel Pentium 4 CPU 3.0G. C language is used for implementation and typically the consumed time for the processing of one group of pictures is about 0.5 s Groups size 8 F=4, T=3

Simulation and Performance

Conclusion The MCTF-based SVC can provide flexibly combined temporal, spatial, SNR and complexity scalability. The channel bit allocation for the video with combined scalability in the MCTF based SVC has never been considered. In this paper, a novel 2-D UEP scheme is proposed for this new technology, which can properly allocate the channel protection bits to the combined temporal and SNR scalable units. We apply GA to solve the optimization problem. The scheme is compared with other four methods under different channel conditions for a variety of video sequences. The simulation results demonstrate the advantage of our proposed scheme.