방송공학회논문지 (Journal of Broadcast Engineering)

  • 제23권1호
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  • Pages.138-145
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  • 2018
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  • 1226-7953(pISSN)
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  • 2287-9137(eISSN)
한국방송∙미디어공학회 (The Korean Institute of Broadcast and Media Engineers)
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프레임 율 향상을 위한 분산 및 적응적 탐색영역을 이용한 움직임 추정 알고리듬

Motion Estimation Algorithm Using Variance and Adaptive Search Range for Frame Rate Up-Conversion

  • 유송현 (한양대학교 전자컴퓨터통신공학과) ;
  • 정제창 (한양대학교 전자컴퓨터통신공학과)
  • Yu, Songhyun (Department of Electronics and Computer Engineering, Hanyang University) ;
  • Jeong, Jechang (Department of Electronics and Computer Engineering, Hanyang University)
  • 투고 : 2017.11.13
  • 심사 : 2017.11.28
  • 발행 : 2018.01.30
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초록

본 논문에서는 움직임 추정을 이용한 새로운 프레임 율 향상 변환 알고리듬을 제안한다. 제안 된 알고리듬은 더 정확한 움직임 벡터를 찾기 위해 움직임 추정 방법에서 오차의 분산을 추가적으로 이용한다. 그런 다음, 이웃 움직임 벡터들의 분산 및 현재 움직임 벡터와 이웃하는 평균 움직임 벡터 간의 분산을 사용하여 잘못 찾아진 움직임 벡터를 탐색한다. 탐색된 벡터들은 8 개의 이웃 움직임 벡터의 가중 합에 의해 수정된다. 또한, 보다 정확한 움직임 벡터를 찾고 동시에 계산 복잡도를 줄일 수 있는 적응적 탐색 영역 결정 알고리듬을 제안한다. 결과적으로, 제안하는 알고리듬은 기존의 알고리듬들에 비해 평균 최대 신호 대 잡음 비 (PSNR)와 구조적 유사도 (SSIM)을 각각 1.44dB 및 0.129까지 향상시켰다.

In this paper, we propose a new motion estimation algorithm for frame rate up-conversion. The proposed algorithm uses the variance of errors in addition to SAD in motion estimation to find more accurate motion vectors. Then, it decides which motion vectors are wrong using the variance of neighbor motion vectors and the variance between current motion vector and neighbor's average motion vector. Next, incorrect motion vectors are corrected by weighted sum of eight neighbor motion vectors. Additionally, we propose adaptive search range algorithm, so we can find more accurate motion vectors and reduce computational complexity at the same time. As a result, proposed algorithm improves the average peak signal-to-noise ratio and structural similarity up to 1.44 dB and 0.129, respectively, compared with previous algorithms.

키워드

참고문헌

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