Jie-Bin Xu, CityU Image Process. Lab., City Univ. of Hong Kong, Hong Kong
Lai-Man Po, CityU Image Process. Lab., City Univ. of Hong Kong, Hong Kong
Most of the fast block matching algorithms (BMAs) use the origin as the initial center of the search. To improve the accuracy of the fast BMAs, a new prediction model (PM) search algorithm is proposed. Based on the spatial correlation of motion and the fast center-biased BMA, the four causal neighbour blocks are chosen to predict the starting search point and then the center-biased BMA is used to find the final motion vector as the global minimum is closer to the predicted center. Experimental results show that the proposed prediction model improves the performance of most fast BMAs such as the new three-step search and the four-step search, in terms of the motion compensation errors. In addition, the average computational requirement is also reduced.
Index Terms:
image matching; prediction model search algorithm; fast block motion estimation; block matching algorithms; spatial correlation; fast center-biased BMA; causal neighbour blocks; starting search point; center-biased BMA; final motion vector; global minimum; experimental results; performance; three-step search; four-step search; motion compensation errors; computational requirement reduction; video compression
Citation:
Jie-Bin Xu, Lai-Man Po, Chok-Kwan Cheung, "A new prediction model search algorithm for fast block motion estimation," icip, vol. 3, pp.610, 1997 International Conference on Image Processing (ICIP'97) - Volume 3, 1997
PURCHASE ARTICLE: $19
IEEE Xplore Subscribers
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb