TY - GEN
T1 - Fully utilized and low design effort architecture for H.264/AVC intra predictor generation
AU - Huang, Yiqing
AU - Liu, Qin
AU - Ikenaga, Takeshi
PY - 2009/12/1
Y1 - 2009/12/1
N2 - Fully exploiting the spatial feature of image makes H.264/ AVC standard superior in intra prediction part. However, when hardware is considered, full support of all intra modes will cause high design effort, especially for large image size. In this paper, we propose a low design effort solution for intra predictor generation, which is the most significant part in intra engine. Firstly, one parallel processing flow is given out, which achieves 37.5% reduction of processing time. Secondly, a fully utilized predictor generation architecture is given out, which saves 77.5% cycles of original one. With 30.11k gates at 200MHz, our design can support full-mode intra prediction for real-time processing of 4k×2k@60fps.
AB - Fully exploiting the spatial feature of image makes H.264/ AVC standard superior in intra prediction part. However, when hardware is considered, full support of all intra modes will cause high design effort, especially for large image size. In this paper, we propose a low design effort solution for intra predictor generation, which is the most significant part in intra engine. Firstly, one parallel processing flow is given out, which achieves 37.5% reduction of processing time. Secondly, a fully utilized predictor generation architecture is given out, which saves 77.5% cycles of original one. With 30.11k gates at 200MHz, our design can support full-mode intra prediction for real-time processing of 4k×2k@60fps.
KW - H.264/AVC
KW - Hardware Architecture
KW - Intra Prediction
UR - http://www.scopus.com/inward/record.url?scp=77249113242&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77249113242&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-11301-7_78
DO - 10.1007/978-3-642-11301-7_78
M3 - Conference contribution
AN - SCOPUS:77249113242
SN - 3642113001
SN - 9783642113000
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 737
EP - 742
BT - Advances in Multimedia Modeling - 16th International Multimedia Modeling Conference, MMM 2010, Proceedings
T2 - 16th International Multimedia Modeling Conference on Advances in Multimedia Modeling, MMM 2010
Y2 - 6 October 2010 through 8 October 2010
ER -