Journal of the Institute of Convergence Signal Processing (융합신호처리학회논문지)

The Korea Institute of Convergence Signal Processing (한국융합신호처리학회)
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Fast Motion Estimation Algorithm Using Importance of Search Range and Adaptive Matching Criterion

탐색영역의 중요도와 적응적인 매칭기준을 이용한 고속 움직임 예측 알고리즘

  • Received : 2015.06.22
  • Accepted : 2015.08.06
  • Published : 2015.10.30
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Abstract

In this paper, we propose a fast motion estimation algorithm which is important in the performance of video encoding. Conventional fast motion estimation algorithms have serious problems of low prediction quality in some frames and still much computation. In the paper, we propose an algorithm that reduces unnecessary computations only, while keeping prediction quality almost similar to that of the full search. The proposed algorithm uses distribution of probability of motion vectors, divides search range into several groups according to its importance, and applies adaptive block matching criteria for each group of search range. The proposed algorithm takes only 3~5% in computational amount and has decreased prediction quality about 0~0.01dB compared with the fast full search algorithm.

본 논문에서는 비디오 압축에서 성능의 중요한 요소인 움직임 예측을 위한 고속 알고리즘을 제안한다. 기존의 고속 움직임 예측 방법들은 연산량 감축으로 인하여 프레임에 따라 심각한 예측화질 저하의 문제점과 여전히 많은 연산량의 문제점을 가지고 있다. 본 논문에서는 전영역 탐색기반의 방법에 비하여 예측화질은 거의 같게 유지하면서 불필요한 계산량을 현저히 줄이는 알고리즘을 제안한다. 제안하는 방법은 움직임 벡터의 확률분포를 이용하여 탐색영역을 중요도 별로 나누고 적응적인 매칭기준을 이용하여 예측화질은 유지하면서 불필요한 계산만을 줄일 수 있는 방법이다. 제안한 알고리즘은 기존의 전영역 탐색방법과 비교하여 예측 화질의 저하가 0.01dB 이하이며, 사용되는 계산량은 3~5%이내이다. 제안한 알고리즘은 MPEG-4 AVC 및 H.265를 이용하는 실시간 비디오 압축 응용분야에 유용하게 사용될 수 있다.

Keywords

References

  1. F. Dufaus and F. Moscheni, "Motion Estimation Techniques for Digital TV: A Review and a New Contribution," Proceeding of IEEE, Vol. 83, No. 3, pp. 858-876, 1995. https://doi.org/10.1109/5.387089
  2. J. Kim and T. Choi, "Adaptive Matching Scan Algorithm based on Gradient Magnitude for Fast Full search in Motion Estimation," IEEE Transactions on Consumer Electronics, Vol. 45, No. 3pp. 762-772, 1999. https://doi.org/10.1109/30.793593
  3. F. Cheng and S. Sun, "New Fast and Efficient Two-Step Search algorithm for Block Motion Estimation," IEEE Transactions on Circuits System for Video Technology, Vol. 9, No. 7, pp. 977-983, 1999. https://doi.org/10.1109/76.795049
  4. C. Zhu, X. Lin, and L. Chau, "Hexagon Based Search Pattern for Fast Block Motion Estimation," IEEE Transactions on Circuits System for Video Technology, Vol. 12, No. 7, pp. 349-355, 2002. https://doi.org/10.1109/TCSVT.2002.1003474
  5. W. Li and E. Salari, "Successive Elimination Algorithm for Motion Estimation," IEEE Transactions on Image Processing, Vol. 4, No. 1, pp. 105-107, 1995. https://doi.org/10.1109/83.350809
  6. M.Z. Coban and R.M. Mersereau, "A Fast Exhaustive Search Algorithm for Rate-Constrained Motion Estimation," IEEE Transactions on Image Processing, Vol. 7, No. 7, pp. 769-773, 1998. https://doi.org/10.1109/83.668031
  7. H. Wang and R. Mersereau, "Fast Algorithms for the Estimation of Motion Vectors," IEEE Transactions on Image Processing, Vol. 8, No. 3, pp. 435-438, 1999. https://doi.org/10.1109/83.748899
  8. X.Q. Gao, C.J. Duanmu, and C.R. Zou, "A Multilevel Successive Elimination Algorithm for Block Matching Motion Estimation," IEEE Transactions on Image Processing, Vol. 9, No. 3, pp. 501-504, 2000. https://doi.org/10.1109/83.826786
  9. T.G. Ahn, Y.H. Moon, and J.H. Kim, "Fast Full-Search Motion Estimation based on Multilevel Successive Elimination Algorithm," IEEE Transactions on Circuits and System for Video Technology, Vol. 14, No. 11, pp. 1265-1269, 2004. https://doi.org/10.1109/TCSVT.2004.835146
  10. J. Kim, S. Byun, Y. Kim, and B. Ahn, "Fast Full Search Motion Estimation Algorithm Using Early Detection of Impossible Candidate Vectors," IEEE Transactions on Signal Processing, Vol. 50, No. 9, pp. 2355-2365, 2002. https://doi.org/10.1109/TSP.2002.801888
  11. H.264/AVC reference software, http://iphome.hhi.de/suehring/tml/download/old_jm/
  12. S. Jin and H. Lee, "Fast Partial Distortion Elimination Algorithm based on Hadamard Probability Model," IEE Electron. Letters, Vol. 44, No. 1, pp. 17-19, 2008. https://doi.org/10.1049/el:20082872