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움직임벡터차에 기반한 고속 움직임 추정 방법

Fast Motion Estimation Method Based on Motion Vector Differences

  • 강현수 (충북대학교 정보통신공학부)
  • 투고 : 2011.01.11
  • 심사 : 2011.03.14
  • 발행 : 2011.05.28

초록

본 논문은 움직임벡터차의 확률을 이용하여 움직임 탐색 범위를 결정하는 새로운 고속 움직임 추정 방법을 제안한다. 제안된 방법은 일종의 적응적 탐색영역 방법이다. 움직임벡터차의 분포에 대한 조사하고 그 분포의 파라미터를 최대우도추정방법으로 추정한다. 이 추정된 분포를 이용하여 탐색 범위는 움직임벡터차의 지정된 확률에 의해 효과적으로 제한될 수 있음을 보인다. 실험적으로 제안된 방법의 성능이 화질면에서 전역탐색법과 유사하며 복잡도 면에서는 중대한 감소를 입증하였다. 뿐만 아니라, 제안된 방법이 기존의 적응적 탐색영역 방법에 비해 훨씬 더 효과적으로 탐색영역을 결정함을 보여주었다.

This paper presents a new fast motion estimation method where search ranges are determined by the probabilities of motion vector differences (MVDs), which is an adaptive/dynamic search range (ASR) method. The MVDs' distribution is investigated and its parameter is estimated by the maximum likelihood estimator. With the estimated distribution, we show that the search ranges can be efficiently restricted by a prefixed probability for MVDs. Experimental results showed that the performance of the proposed method is very similar to that of the full search algorithm in PSNR but it enables significant reduction in the computational complexity. In addition, they revealed that the proposed method determine the search ranges much more efficiently than the conventional ASR methods.

키워드

참고문헌

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