TY - GEN
T1 - Inter-frame and inter-layer motion prediction during fast block motion estimation in MCTF
AU - Karunakar, A. K.
AU - Pai, M. M Manohara
PY - 2008
Y1 - 2008
N2 - The motion compensated temporal filtering (MCTF) using 5/3 LeGall bi orthogonal wavelet filter requires bidirectional motion estimation (ME) that is computationally intensive. Hence encoder of Scalable Video Coder(SVC) becomes very slow. This paper proposes Motion Prediction technique for Fast Block Based ME during MCTF in SVC. The technique exploits center biased characteristics of motion vectors. It applies coarse and fine search of any fast block based ME, only to the first pair of frames in a group of pictures (GOP). The generated motion vectors (MVs) are supplied to the next consecutive frames and even to subsequent temporal levels, that is used to initiate the fine search. The technique significantly reduces the number of blocks that undergoes ME in a GOP and hence reduces computational complexity of ME in MCTF. The proposed algorithm is implemented in MC-EZBC and there is no visible variations in the quality of the decoded video.
AB - The motion compensated temporal filtering (MCTF) using 5/3 LeGall bi orthogonal wavelet filter requires bidirectional motion estimation (ME) that is computationally intensive. Hence encoder of Scalable Video Coder(SVC) becomes very slow. This paper proposes Motion Prediction technique for Fast Block Based ME during MCTF in SVC. The technique exploits center biased characteristics of motion vectors. It applies coarse and fine search of any fast block based ME, only to the first pair of frames in a group of pictures (GOP). The generated motion vectors (MVs) are supplied to the next consecutive frames and even to subsequent temporal levels, that is used to initiate the fine search. The technique significantly reduces the number of blocks that undergoes ME in a GOP and hence reduces computational complexity of ME in MCTF. The proposed algorithm is implemented in MC-EZBC and there is no visible variations in the quality of the decoded video.
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U2 - 10.1007/978-3-540-85891-1_18
DO - 10.1007/978-3-540-85891-1_18
M3 - Conference contribution
AN - SCOPUS:55249085836
SN - 3540858903
SN - 9783540858904
VL - 5188 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 150
EP - 154
BT - Visual Information Systems
T2 - 10th International Conference on Visual Information Systems, VISUAL 2008
Y2 - 11 September 2008 through 12 September 2008
ER -