Name
Abstract | ||
|---|---|---|
A novel Linear Hashtable Method Predicted Hexagonal Search (LHMPHS) method for block based motion compensation is proposed. Fast block matching algorithms use the origin as the initial search center, which often does not track motion very well. To improve the accuracy of the fast BMA's, we employ a predicted starting search point, which reflects the motion trend of the current block. The predicted search centre is found closer to the global minimum. Thus the center-biased BMA's can be used to find the motion vector more efficiently. The performance of the algorithm is evaluated by using standard video sequences, considers the three important metrics: The results show that the proposed algorithm enhances the accuracy of current hexagonal algorithms and is better than Full Search, Logarithmic Search etc. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11538059_15 | ICIC (1) |
Keywords | Field | DocType |
full search,initial search center,predicted hexagonal search,motion trend,center-biased bma,search point,hexagonal search algorithm,motion compensation,motion vector,current block,search centre,search algorithm,block matching algorithm | Data compression ratio,Search algorithm,Pattern recognition,Interpolation search,Computer science,Motion compensation,Algorithm,Artificial intelligence,Motion estimation,Binary search algorithm,Logarithm,Motion vector | Conference |
Volume | ISSN | ISBN |
3644 | 0302-9743 | 3-540-28226-2 |
Citations | PageRank | References |
3 | 0.52 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yunsong Wu | 1 | 6 | 3.07 |
| Graham Megson | 2 | 13 | 4.03 |