전자공학회논문지 (Journal of the Institute of Electronics and Information Engineers)

  • 제51권12호
  • /
  • Pages.130-139
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  • 2014
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  • 2287-5026(pISSN)
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  • 2288-159X(eISSN)
대한전자공학회 (The Institute of Electronics and Information Engineers)
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카메라 움직임 추정 및 패치 기반 디컨볼루션을 이용한 동영상의 번짐 현상 제거 방법

Video Deblurring using Camera Motion Estimation and Patch-wise Deconvolution

  • 정우진 (한양대학교 컴퓨터공학과) ;
  • 박진욱 (한양대학교 컴퓨터공학과) ;
  • 이종민 (한양대학교 컴퓨터공학과) ;
  • 송태언 (삼성탈레스 전자광학체계그룹) ;
  • 최원주 (삼성탈레스 전자광학체계그룹) ;
  • 문영식 (한양대학교 컴퓨터공학과)
  • Jeong, Woojin (Dept. of Computer Science & Engineering, Hanyang University) ;
  • Park, Jin Wook (Dept. of Computer Science & Engineering, Hanyang University) ;
  • Lee, Jong Min (Dept. of Computer Science & Engineering, Hanyang University) ;
  • Song, Tae Eun (Optronics System Group, Samsung Thales) ;
  • Choi, Wonju (Optronics System Group, Samsung Thales) ;
  • Moon, Young Shik (Dept. of Computer Science & Engineering, Hanyang University)
  • 투고 : 2014.08.12
  • 심사 : 2014.11.30
  • 발행 : 2014.12.25
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초록

동영상 촬영 시 급격한 카메라의 흔들림은 의도하지 않은 번짐 현상을 발생시켜 동영상의 품질을 낮추는 원인이 된다. 따라서 본 논문에서는 동영상의 품질을 높이기 위해 동영상에서 카메라 흔들림으로 인해 발생한 번짐 현상을 제거하는 방법을 제안한다. 제안하는 방법은 매 프레임 별로 이루어진다. 각 프레임마다 이전 프레임과 현재 프레임, 다음 프레임을 이용하여 카메라 움직임을 계산한다. 그리고 카메라의 움직임을 바탕으로 점 확산 함수를 계산하고 프레임을 패치 단위로 쪼개어 패치별 번짐 현상을 제거한다. 이때 품질을 높이기 위하여 번짐 영상으로부터 외곽선을 예측하는 방법을 사용한다. 번짐 현상이 제거된 패치는 다시 하나의 프레임으로 합한다. 실험 결과를 통해 제안하는 방법이 동영상에서의 카메라 흔들림으로 인한 번짐 현상을 효과적으로 제거함을 확인하였다.

Undesired camera shaking can make a blur effect, which causes a degradation of video quality. We propose an efficient method of removing the blur effects on video captured from a single camera. The proposed method has a sequential process that is applied to each frame. The first stage is to estimate the camera motion for each frame. In order to estimate the camera motion, we compute the optical flow using 3 consecutive frames. Then a patch-wise image deconvolution is applied. During the deconvolution, edge prediction is used to improve the quality of image deconvolution. After patch-wise image deconvolution, deblurred patches are integrated into an image to produce a deblurred frame. The above process is performed for each frame. The experimental result shows that the proposed method removes the blur effect efficiently.

키워드

참고문헌

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