@article{(Open Science Index):https://publications.waset.org/pdf/6910,
	  title     = {Motion Prediction and Motion Vector Cost Reduction during Fast Block Motion Estimation in MCTF},
	  author    = {Karunakar A K and  Manohara Pai M M},
	  country	= {},
	  institution	= {},
	  abstract     = {In 3D-wavelet video coding framework temporal
filtering is done along the trajectory of motion using Motion
Compensated Temporal Filtering (MCTF). Hence computationally
efficient motion estimation technique is the need of MCTF. In this
paper a predictive technique is proposed in order to reduce the
computational complexity of the MCTF framework, by exploiting
the high correlation among the frames in a Group Of Picture (GOP).
The proposed technique applies coarse and fine searches of any fast
block based motion estimation, only to the first pair of frames in a
GOP. The generated motion vectors are supplied to the next
consecutive frames, even to subsequent temporal levels and only fine
search is carried out around those predicted motion vectors. Hence
coarse search is skipped for all the motion estimation in a GOP
except for the first pair of frames. The technique has been tested for
different fast block based motion estimation algorithms over different
standard test sequences using MC-EZBC, a state-of-the-art scalable
video coder. The simulation result reveals substantial reduction (i.e.
20.75% to 38.24%) in the number of search points during motion
estimation, without compromising the quality of the reconstructed
video compared to non-predictive techniques. Since the motion
vectors of all the pair of frames in a GOP except the first pair will
have value ±1 around the motion vectors of the previous pair of
frames, the number of bits required for motion vectors is also
reduced by 50%.},
	    journal   = {International Journal of Electronics and Communication Engineering},
	  volume    = {4},
	  number    = {3},
	  year      = {2010},
	  pages     = {461 - 466},
	  ee        = {https://publications.waset.org/pdf/6910},
	  url   	= {https://publications.waset.org/vol/39},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 39, 2010},
	}