TY - JOUR
T1 - Motion feature and hadamard coefficient-based fast multiple reference frame motion estimation for H.264
AU - Liu, Zhenyu
AU - Li, Lingfeng
AU - Song, Yang
AU - Li, Shen
AU - Goto, Satoshi
AU - Ikenaga, Takeshi
N1 - Funding Information:
Manuscript received May 24, 2007; revised September 28, 2007. This work was supported by fund from the CREST JST. This paper was recommended by Associate Editor L.-G. Chen.
PY - 2008/5
Y1 - 2008/5
N2 - In the state-of-the-art video coding standard, H.264/AVC, the encoder is allowed to search for its prediction signals among a large number of reference pictures that have been decoded and stored in the decoder to enhance its coding efficiency. Therefore, the computation complexity of the motion estimation (ME) increases linearly with the number of reference picture. Many fast multiple reference frame ME algorithms have been proposed, whose performance, however, will be considerably degraded in the hardwired encoder design due to the macroblock (MB) pipelining architecture. Considering the limitations of the traditional four-stage MB pipelining architecture, two fast multiple reference frame ME algorithms are proposed here. First, on the basis of mathematical analysis, which reveals that the efficiency of multiple reference frames will be degraded by the relative motion between the camera and the objects, for the slow-moving MB, the authors adopt the multiple reference frames but reduce their search range. On the other hand, for the fast-moving MB, the first previous reference frame is used with the full search range during the ME processing. The mutually exclusive feature between the large search range and the multiple reference frames makes the computation saving performance of the proposed algorithm insensitive to the nature of video sequence. Second, following the Hadamard transform coefficient-based all_zeros block early detection algorithm, two early termination criteria are proposed. These methods ensure the pronounced computation saving efficiency when the encoded video has strong spatial homogeneity or temporal stationarity. Experimental results show that 72.7%93.7% computation can be saved by the proposed fast algorithms with an average of 0.0899 dB coding quality degradation. Moreover, these fast algorithms can be combined with fast block matching algorithms to further improve their speedup performance.
AB - In the state-of-the-art video coding standard, H.264/AVC, the encoder is allowed to search for its prediction signals among a large number of reference pictures that have been decoded and stored in the decoder to enhance its coding efficiency. Therefore, the computation complexity of the motion estimation (ME) increases linearly with the number of reference picture. Many fast multiple reference frame ME algorithms have been proposed, whose performance, however, will be considerably degraded in the hardwired encoder design due to the macroblock (MB) pipelining architecture. Considering the limitations of the traditional four-stage MB pipelining architecture, two fast multiple reference frame ME algorithms are proposed here. First, on the basis of mathematical analysis, which reveals that the efficiency of multiple reference frames will be degraded by the relative motion between the camera and the objects, for the slow-moving MB, the authors adopt the multiple reference frames but reduce their search range. On the other hand, for the fast-moving MB, the first previous reference frame is used with the full search range during the ME processing. The mutually exclusive feature between the large search range and the multiple reference frames makes the computation saving performance of the proposed algorithm insensitive to the nature of video sequence. Second, following the Hadamard transform coefficient-based all_zeros block early detection algorithm, two early termination criteria are proposed. These methods ensure the pronounced computation saving efficiency when the encoded video has strong spatial homogeneity or temporal stationarity. Experimental results show that 72.7%93.7% computation can be saved by the proposed fast algorithms with an average of 0.0899 dB coding quality degradation. Moreover, these fast algorithms can be combined with fast block matching algorithms to further improve their speedup performance.
KW - H.264/AVC
KW - Motion estimation (ME)
KW - Motion vector (MV)
KW - Multiple reference frames
KW - VLSI
KW - Video coding
KW - Video signal processing
UR - http://www.scopus.com/inward/record.url?scp=43049167188&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=43049167188&partnerID=8YFLogxK
U2 - 10.1109/TCSVT.2008.918844
DO - 10.1109/TCSVT.2008.918844
M3 - Article
AN - SCOPUS:43049167188
SN - 1051-8215
VL - 18
SP - 620
EP - 632
JO - IEEE Transactions on Circuits and Systems for Video Technology
JF - IEEE Transactions on Circuits and Systems for Video Technology
IS - 5
M1 - 4454352
ER -