Paper Info
Title
Low-Complexity Hybrid-Domain H.264/Svc To H.264/Avc Spatial Transcoding With Drift Compensation For Videoconferencing
Abstract
As an extension of H.264/AVC, Scalable Video Coding (SVC) provides the ability to adapt to heterogeneous networks and user-end requirements, which offers great scalability in multi-point applications such as videoconferencing. However, transcoding between SVC and AVC becomes necessary due to the existence of legacy AVC-based systems. The straightforward full re-encoding method requires great computational cost, and the fast SVC-to-AVC spatial transcoding techniques have not been thoroughly investigated yet. This paper proposes a low-complexity hybrid-domain SVC-to-AVC spatial transcoder with drift compensation, which provides even better coding efficiency than the full re-encoding method. The macroblocks (MBs) of input SVC bitstream are divided into two types, and each type is suitable for pixel- or transform-domain processing respectively. In the pixel-domain transcoding, a fast re-encoding method is proposed based on mode mapping and motion vector (MV) refinement. In the transform-domain transcoding, the quantized transform coefficients together with other motion data are reused directly to avoid re-quantization loss. The drift problem caused by proposed transcoder is solved by compensation techniques for I frame and P frame respectively. Simulation results show that proposed transcoder achieves averagely 96.4% time reduction compared with the full re-encoding method, and outperforms the reference methods in coding efficiency.
Year
DOI
Venue
2013
10.1587/transfun.E96.A.2142
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES
Keywords
Field
DocType
SVC-to-AVC transcoding, spatial scalability, hybrid-domain, drift compensation, videoconferencing
Transcoding,Computer architecture,Spatial scalability,Real-time computing,Theoretical computer science,Videoconferencing,Mathematics
Journal
Volume
Issue
ISSN
E96A
11
0916-8508
Citations 
PageRank 
References 
0
0.34
20
Authors
3
Name
Order
Citations
PageRank
Lei Sun12615.36
Zhenyu Liu217223.22
Takeshi Ikenaga3618125.50