Name
Abstract | ||
|---|---|---|
Motion estimation (ME) is one of the key elements in video coding standard which eliminates the temporal redundancy by using a motion vector (MV) to indicate the best match between the current frame and reference frame. A coarse to fine process is taken to find the best MV. First of all, integer-pixel ME finds a coarse MV and followed by the sub-pixel ME around the best integer-pixel point. The sub-pixel ME plays an important role in improving the coding efficiency. However, the computational complexity of searching one sub-pixel point is much higher than the integer-pixel point searching because of the interpolation and Hadamard transform operation. In this paper, an accurate optimal sub-pixel position prediction algorithm is presented. With the information of the 8 neighboring integer-pixel points, the optimal sub-pixel position is predicted directly without explicitly solving model parameters. Moreover, an outlier rejection scheme is applied to improve the robustness of the proposed algorithm. Experimental results show that the proposed algorithm outperforms the state of the art interpolation-freesub-pixel ME algorithms. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICIP.2013.6738364 | ICIP |
Keywords | Field | DocType |
motion vector,sub-pixel motion estimation,telecommunication standards,reference frame,robust interpolation-free approach,interpolation-free,current frame,video coding standard,motion estimation,computational complexity,sub-pixel accuracy motion estimation,video coding,temporal redundancy,integer-pixel point,vectors | Reference frame,Computer vision,Block-matching algorithm,Quarter-pixel motion,Pattern recognition,Computer science,Interpolation,Motion compensation,Inter frame,Artificial intelligence,Motion estimation,Motion vector | Conference |
ISSN | Citations | PageRank |
1522-4880 | 4 | 0.49 |
References | Authors | |
9 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Dai | 1 | 18 | 3.46 |
| Oscar C. Au | 2 | 1592 | 176.54 |
| Wenjing Zhu | 3 | 20 | 3.74 |
| Wei Hu | 4 | 244 | 22.01 |
| Pengfei Wan | 5 | 45 | 9.40 |
| Jiali Li | 6 | 49 | 9.29 |