• Title/Summary/Keyword: Half-Pixel Motion Estimation

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Motion Estimation Skipping Technique for Fast Motion Estimation (고속 움직임 추정을 위한 움직임 추정 생략 기법)

  • 강현수;박성모
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.7C
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    • pp.726-732
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    • 2003
  • The paper proposes a motion estimation (ME) technique to reduce computational complexity. It is achieved by skipping ME process for macro-blocks decided to be in no need of the operation. Thus, it is called ME skipping technique(MEST). In general, the ME is composed of integer pixel precision ME (IME) followed by half pixel precision ME (HME). The MEST is performed just before an IME process and makes a decision on skipping the IME process according to a criterion based on ME errors of adjacent macro-blocks (MBs) already encoded. When the IME process for a MB is decided to be skipped, which is called ME skip mode, the IME process is skipped and the integer pixel precision motion vector of the MB is just replaced by a predicted vector and used as the input of HME. On the other hands, the IME processes for MBs in ME non-skip mode are not skipped but normally performed. Accordingly, the MEST is very effective to reduce computational complexity when MBs in ME skip mode is abundant. In addition, when the MEST is applied to video encoder, it contributes to more accurate rate control and more robusaess for channel errors. It is experimentally shown that the MEST has the above advantages while maintaining good reconstructed image quality.

East Half-Pixel Motion Estimation Based on SAD Curve Modeling (SAD 함수 모델링을 이용한 고속 반화소 추정 알고리즘)

  • 이윤구;최부림;나종범
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.1924-1927
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    • 2003
  • 많은 고속 정화소 움직임 추정 알고리즘이 개발됨에 따라, 최근에는 10개의 탐색점만으로 정화소 움직임벡터를 찾을 수 있게 되었다. 반면에, 반화소 움직임 추정에서는 정화소 움직임 벡터주변의 8 개의 반화소 탐색점을 검색해야 한다 그러므로 반화소 움직임 추정 알고리즘의 계산량을 줄일 필요성이 생기게 되었다 본 논문에서는 directional search 와 SAD 함수의 선형 모델링을 이용한 고속 반화소 움직임 추정 알고리즘을 제안한다 제안된 알고리즘은 PSNR 열화 없이 2.21 개의 탐색만으로도 움직임 벡터를 찾을 수 있게 해준다 특히, 조절 가능한 파라미터를 이용하면. 약간의 PSNR 감소와 함께 0.34개의 탐색만으로 움직임 벡터를 추정을 할 수 있게 해준다.

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