TY - GEN
T1 - Motion-based adaptive GOP algorithms for efficient H.264/AVC compression
AU - Ding, Jun Ren
AU - Lin, Ji Kun
AU - Yang, Jar Ferr
PY - 2006
Y1 - 2006
N2 - H.264/AVC provides several advanced features such as improved coding efficiency and error robustness for video storage and transmission. In this paper, to further improve the coding quality for encoding possible scene changes and fast variation sequences, we propose a new adaptive GOP scheme that uses the existing motion vectors and motion residuals. The proposed scheme effectively identifies the H.264/AVC coding core {I, P} frames using a statistical table that improves the coding efficiency for changed scene sequences and different video content variance. Simulation results show that the proposed adaptive GOP scheme can increase PSNR 0.65 dB on average and achieve a 92% correct rate for scene change detection from the original H.264 reference software JM10.1 operated in the fixed GOP size.
AB - H.264/AVC provides several advanced features such as improved coding efficiency and error robustness for video storage and transmission. In this paper, to further improve the coding quality for encoding possible scene changes and fast variation sequences, we propose a new adaptive GOP scheme that uses the existing motion vectors and motion residuals. The proposed scheme effectively identifies the H.264/AVC coding core {I, P} frames using a statistical table that improves the coding efficiency for changed scene sequences and different video content variance. Simulation results show that the proposed adaptive GOP scheme can increase PSNR 0.65 dB on average and achieve a 92% correct rate for scene change detection from the original H.264 reference software JM10.1 operated in the fixed GOP size.
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U2 - 10.2991/jcis.2006.12
DO - 10.2991/jcis.2006.12
M3 - Conference contribution
AN - SCOPUS:33847695242
SN - 9078677015
SN - 9789078677017
T3 - Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006
BT - Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006
T2 - 9th Joint Conference on Information Sciences, JCIS 2006
Y2 - 8 October 2006 through 11 October 2006
ER -