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A Partial Norm Based Early Rejection Algorithm for Fast Motion Estimation
Won-Gi HONG Young-Ro KIM Tae-Myoung OH Sung-Jea KO
Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Vol.E88-A
No.3
pp.626-632 Publication Date: 2005/03/01 Online ISSN:
DOI: 10.1093/ietfec/e88-a.3.626 Print ISSN: 0916-8508 Type of Manuscript: Special Section PAPER (Special Section on Adaptive Signal Processing and Its Applications) Category: Keyword: block motion estimation, successive elimination algorithm, halfway-stop technique, partial norms,
Full Text: PDF(606.7KB)>>
Summary:
Recently, many algorithms have been proposed for fast full search motion estimation. Among them, successive elimination algorithm (SEA) and its modified algorithms significantly speed up the performance of the full search algorithm. By introducing the inequality equation between the norm and the mean absolute difference (MAD) of two matching blocks, the SEA can successively eliminate invalid candidate blocks without any loss in estimation accuracy. In this paper, we propose a partial norm based early rejection algorithm (PNERA) for fast block motion estimation. The proposed algorithm employs the sum of partial norms from several subblocks of the block. Applying the sum of partial norms to the inequality equation, we can significantly reduce the computational complexity of the full search algorithm. In an attempt to reduce the computational load further, the modified algorithms using partial norm distortion elimination (PNDE) and subsampling methods are also proposed. Experimental results show that the proposed algorithm is about 4 to 9 times faster than the original exhaustive full search, and is about 3 to 4 times faster than the SEA.
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