• Title/Summary/Keyword: notiobn estimation

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AMSEA: Advanced Multi-level Successive Elimination Algorithms for Motion Estimation (움직임 추정을 위한 개선된 다단계 연속 제거 알고리즘)

  • Jung, Soo-Mok;Park, Myong-Soon
    • Journal of KIISE:Software and Applications
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    • v.29 no.1_2
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    • pp.98-113
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    • 2002
  • In this paper, we present advanced algorithms to reduce the computations of block matching algorithms for motion estimation in video coding. Advanced multi-level successive elimination algorithms(AMSEA) are based on the Multi-level successive elimination algorithm(MSEA)[1]. The first algorithm is that when we calculate the sum of absolute difference (SAD) between the sum norms of sub-blocks in MSEA, we use the partial distortion elimination technique. By using the first algorithm, we can reduce the computations of MSEA further. In the second algorithm, we calculate SAD adaptively from large value to small value according to the absolute difference values between pixels of blocks. By using the second algorithm, the partial distortion elimination in SAD calculation can occur early. So, the computations of MSEA can be reduced. In the third algorithm, we can estimate the elimination level of MSEA. Accordingly, the computations of the MSEA related to the level lower than the estimated level can be reduced. The fourth algorithm is a very fast block matching algorithm with nearly 100% motion estimation accuracy. Experimental results show that AMSEA are very efficient algorithms for the estimation of motion vectors.