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적응적 움직임 추정 기법을 활용하는 새로운 움직임 보상 프레임 보간 알고리즘

A New Motion Compensated Frame Interpolation Algorithm Using Adaptive Motion Estimation

  • Hwang, Inseo (Department of Electrical and Computer Engineering, Ajou University) ;
  • Jung, Ho Sun (Department of Electrical and Computer Engineering, Ajou University) ;
  • Sunwoo, Myung Hoon (Department of Electrical and Computer Engineering, Ajou University)
  • 투고 : 2015.03.17
  • 심사 : 2015.05.30
  • 발행 : 2015.06.25

초록

본 논문에서는 움직임 추정 기법을 적응적으로 사용하는 프레임율 증강 기법인 AME-FRUC (Adaptive Motion Estimation Frame Rate Up-Conversion)을 제안하고자 한다. 제안하는 알고리즘은 영상의 움직임이 적은 영역에서 기존의 EBME (Extended Bilateral Motion Estimation)을 활용하고, 움직임 벡터 정보를 활용하여 관심영역을 결정한다. 관심 영역에서는 제안하는 텍스쳐 정보에 기반한 블록 분할을 활용한 단방향 움직임 추정을 수행하도록 하여 정확도를 높였다. 최종적으로 MCFI (Motion Compensated Frame Interpolation)기법을 움직임 추정 방법에 따라 적용하고 보간 하여 중간 프레임을 생성 한다. 실험 결과를 통해 제안하는 알고리즘이 기존의 FRUC 알고리즘에 비해 최대 68% 적은 SAD 연산으로 3dB 높은 PSNR 성능과 0.07 더 높은 SSIM 성능을 보이는 것을 확인할 수 있다.

In this paper, a new frame rate up conversion (FRUC) algorithm using adaptive motion estimation (AME-FRUC) is proposed. The proposed algorithm performs extended bilateral motion estimation (EBME) conducts motion estimation (ME) processes on the static region, and extract region of interest with the motion vector (MV). In the region of interest block, the proposed AME-FRUC uses the texture block partitioning scheme and the unilateral motion estimation for improving ME accuracy. Finally, motion compensated frame interpolation (MCFI) are adopted to interpolate the intermediate frame in which MCFI is employed adaptively based on ME scheme. Experimental results show that the proposed algorithm improves the PSNR up to 3dB, the SSIM up to 0.07 and 68% lower SAD calculations compared to the EBME and the conventional FRUC algorithms.

키워드

참고문헌

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