The Journal of the Korea Contents Association (한국콘텐츠학회논문지)

The Korea Contents Association (한국콘텐츠학회)
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Effective Frame Rate Up-Conversion Method Using Adaptive Motion Refinement Based on ROI Separation

관심영역 분리에 따른 적응적인 움직임 보정에 기초한 효과적인 프레임 율 증가 기법

  • 이범용 (한밭대학교 정보통신전문대학원) ;
  • 김진수 (한밭대학교 정보통신전문대학원)
  • Received : 2015.08.24
  • Accepted : 2016.01.06
  • Published : 2016.02.28
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Abstract

This paper proposes an effective FRUC (Frame Rate Up-Conversion) technique, which is based on ROI (Region Of Interest) separations and adaptive motion vector refinement. In this paper, in order to overcome the weakness of the EBME (Extended Bi-lateral Motion Estimation) algorithm, which is widely known in FRUC techniques, first, the proposed algorithm performs a bi-directional motion estimation for the complementary asymmetric region. Then, the proposed algorithm classifies each block into ROI or non-ROI block and refine motion vectors in accordance with their block characteristics to have a higher accuracy than the conventional EBME algorithm, specially, for the occlusion regions. The experimental results show that the proposed algorithm can improves 0.59dB on average PSNR as compared to the conventional method.

본 논문에서는 관심영역 분리에 따른 적응적인 움직임 보정에 기초한 효과적인 프레임 율 증가 기법을 제안한다. 기존에 가장 많이 알려진 방법인 확장 양방향 움직임 추정 방법(EBME)의 단점을 극복하기 위해, 제안된 알고리즘은 상호 보완적인 비대칭 영역에 대해 양방향 움직임 추정을 수행한다. 그런 후에, 블록 단위로 움직임이나 변화가 있는 영역을 관심영역으로 분류하고 관심영역의 블록 특성에 따라 움직임 벡터를 세부적으로 보정한다. 제안하는 알고리즘은 기존의 선형적인 움직임에 기초하는 확장 양방향 움직임 추정보다 특히 폐색영역에 대해 효율적인 움직임 추정을 한다. 다양한 테스트 비디오 시퀀스들에 대하여 실험한 결과에 따르면, 제안한 방식은 기존 EBME 대비 평균 0.59dB의 화질 개선을 달성하였음을 보인다.

Keywords

References

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