DocumentCode :
2654895
Title :
Analysis of adaptive algorithm to power aware design for H.264/AVC integer motion estimation engine in HDTV application
Author :
Huang, Yiqing ; Ikenaga, Takeshi
Author_Institution :
Inf. Production & Syst., Waseda Univ., Kitakyushu, Japan
fYear :
2009
fDate :
20-23 Oct. 2009
Firstpage :
163
Lastpage :
166
Abstract :
In this paper, we contribute two reconfigurable integer motion estimation (IME) architectures (namely RSADT and RPPSAD) based on adaptive algorithm. Firstly, based on the pixel difference analysis, the spatial redundancy is further exploited and three subsampling patterns are selected adaptively. Secondly, in order to keep full data reuse, we propose an architecture level data organization for RSADT architecture. For RPPSAD, we apply pixel classification and memory organization to keep full data reuse. An interactive data loading scheme is proposed to reduce power dissipation. Experiments show that, with some extra hardware, our RSADT can averagely achieve 65.86% reduction in processing time; as for RPPSAD, it can save 25.4% to 39.8% power dissipation when processing typical HDTV720p sequences.
Keywords :
high definition television; image classification; motion estimation; reconfigurable architectures; storage management; video coding; H.264/AVC integer motion estimation; HDTV application; RPPSAD architecture; RSADT architecture; adaptive algorithm; architecture level data organization; interactive data loading; memory organization; pixel classification; pixel difference analysis; power aware design; power dissipation; reconfigurable architecture; spatial redundancy; Adaptive algorithm; Algorithm design and analysis; Automatic voltage control; Engines; HDTV; Hardware; Motion estimation; Pattern analysis; Power dissipation; Reconfigurable architectures; Adaptive Algorithm; H.264/AVC; Reconfigurable Architecture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
ASIC, 2009. ASICON '09. IEEE 8th International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-1-4244-3868-6
Electronic_ISBN :
978-1-4244-3870-9
Type :
conf
DOI :
10.1109/ASICON.2009.5351583
Filename :
5351583
Link To Document :
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