TY - GEN
T1 - A Macroblock-Level Rate Control Algorithm for H.264/AVC Video Coding with context-adaptive MAD Prediction Model
AU - Wu, Shuijiong
AU - Wang, Yiqing
AU - Ikenaga, Takeshi
PY - 2009/4/23
Y1 - 2009/4/23
N2 - Rate control (RC) is crucial for video codec to control bit-stream such that the coding efficiency is maximized without violating the constraints imposed by the bandwidth, buffer size and the constant end-to-end delay. To solve MAD dilemma caused by data-dependency between RC and ratedistortion optimization (RDO), a Macroblock (MB) level rate control algorithm with context-adaptive mean absolute difference (MAD) prediction model is proposed in this paper. 2D sliding window combined with temporal ordering is used for model update, and the reference MAD is computed by considering spatial information relativity. Simulations based on JM software show that the proposed model achieves higher peak-signal-noise-ratio (PSNR) and more accurate rate match than the original JVT-G012 algorithm. A gain up to 0.63dB is observed on luminance PSNR, and 0.58dB on PSNR includes both luminance and chrominance components. Average gains are 0.35dB and 0.29dB, respectively. Meanwhile, the average rate mismatch is reduced by 88%.
AB - Rate control (RC) is crucial for video codec to control bit-stream such that the coding efficiency is maximized without violating the constraints imposed by the bandwidth, buffer size and the constant end-to-end delay. To solve MAD dilemma caused by data-dependency between RC and ratedistortion optimization (RDO), a Macroblock (MB) level rate control algorithm with context-adaptive mean absolute difference (MAD) prediction model is proposed in this paper. 2D sliding window combined with temporal ordering is used for model update, and the reference MAD is computed by considering spatial information relativity. Simulations based on JM software show that the proposed model achieves higher peak-signal-noise-ratio (PSNR) and more accurate rate match than the original JVT-G012 algorithm. A gain up to 0.63dB is observed on luminance PSNR, and 0.58dB on PSNR includes both luminance and chrominance components. Average gains are 0.35dB and 0.29dB, respectively. Meanwhile, the average rate mismatch is reduced by 88%.
KW - Context-adaptive prediction
KW - MAD
KW - MB level
KW - Spatial reference computing
KW - Update modeling
UR - http://www.scopus.com/inward/record.url?scp=64849096137&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=64849096137&partnerID=8YFLogxK
U2 - 10.1109/ICCMS.2009.21
DO - 10.1109/ICCMS.2009.21
M3 - Conference contribution
AN - SCOPUS:64849096137
SN - 9780769535623
T3 - Proceedings - 2009 International Conference on Computer Modeling and Simulation, ICCMS 2009
SP - 124
EP - 128
BT - Proceedings - 2009 International Conference on Computer Modeling and Simulation, ICCMS 2009
T2 - 2009 International Conference on Computer Modeling and Simulation, ICCMS 2009
Y2 - 20 February 2009 through 22 February 2009
ER -