DocumentCode :
454933
Title :
Adaptive Mad Prediction and Refined R-Q Model for H.264/AVC Rate Control
Author :
Liu, Y. ; Li, Z.G. ; Soh, Y.C.
Author_Institution :
Centre for Modeling & Control of Complex Syst., Nanyang Technol. Univ.
Volume :
2
fYear :
2006
fDate :
14-19 May 2006
Abstract :
This paper presents an improved rate control scheme for the H.264/AVC video coding scheme. By analyzing the relationship between direct mean absolute difference (MAD) and actual MAD, a new MAD prediction scheme is introduced to enhance traditional linear MAD prediction model, which is unable to predict abrupt MAD fluctuations. Our proposed adaptive model could reduce MAD prediction error by up to 34%. One simple sum bit quadratic R-Q model is also presented to solve the problem caused by inaccurate texture bits estimation of H.264/AVC. With the new MAD prediction model and R-Q model, our proposed scheme could reduce the mismatch between actual frame bits and target frame bits by up to 32%, and the buffer occupancy is much closer to the ideal status. Meanwhile, reconstructed video quality is also improved by up to 0.21 dB at low bitrate
Keywords :
image reconstruction; image texture; video coding; H.264/AVC rate control; adaptive MAD prediction; mean absolute difference; reconstructed video quality; refined RQ model; texture bits estimation; video coding scheme; Adaptive control; Automatic voltage control; Motion compensation; Motion estimation; Predictive models; Programmable control; Quadratic programming; Quantization; Video coding; Video compression;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location :
Toulouse
ISSN :
1520-6149
Print_ISBN :
1-4244-0469-X
Type :
conf
DOI :
10.1109/ICASSP.2006.1660490
Filename :
1660490
Link To Document :
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