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

The Institute of Electronics and Information Engineers (대한전자공학회)
권호 표지
DOI QR코드

DOI QR Code

A Video Deblurring Algorithm based on Sharpness Metric for Uniform Sharpness between Frames

프레임 간 선명도 균일화를 위한 선명도 메트릭 기반의 동영상 디블러링 알고리즘

  • Received : 2012.10.15
  • Published : 2013.04.25
Download PDF
⟨ Previous Next ⟩

Abstract

This paper proposes a video deblurring algorithm which maintains uniform sharpness between frames. Unlike the previous algorithms using fixed parameters, the proposed algorithm keeps uniform sharpness by adjusting parameters for each frame. First, we estimate the initial blur kernel and perform deconvolution, then measure the sharpness of the deblurred image. In order to maintain uniform sharpness, we adjust the regularization parameter and kernel according to the examined sharpness, and perform deconvolution again. The experimental results show that the proposed algorithm achieves outstanding deblurring results while providing consistent sharpness.

본 논문은 동영상 프레임 간 선명도를 균일하게 유지하면서 블러를 제거하는 기법을 제안한다. 고정된 변수들을 이용하는 기존 기법들과 달리, 제안하는 동영상 디블러링 기법은 영상에 따라 디블러 변수들을 조절함으로써 선명도를 균일하게 만들어 준다. 먼저, 입력 프레임의 초기 블러 커널을 추정하고, 디컨볼루션을 수행한 뒤, 선명도를 측정한다. 그리고 균일한 선명도를 유지할 수 있도록 측정된 선명도에 기반하여 정규화 변수와 커널을 조절하고, 다시 디컨볼루션을 수행한다. 실험 결과를 통해 제안 기법이 상당히 균일한 선명도를 유지하면서 디블러링을 수행함을 확인할 수 있다.

Keywords

References

  1. R. Fergus, H. Singh, A. Herzmann, S. T. Reweis, and W. T. Freeman. "Removing camera shake from a single photograph," in Proc. ACM SIGGRAPH, pp. 787-794, 2006.
  2. A. Levin, Y. Weiss, F, Durand, and W. T. Freeman, "Understanding and evaluating blind deconvolution algorithms," in Proc. CVPR, 2009.
  3. L. Xu and J. Jia, "Two-phase kernel estimation for robust motion deblurring," in Proc. ECCV, pp. 157-170, 2010.
  4. S. Cho and S. Lee, "Fast motion deblurrin," ACM Trans. Graphics, vol. 28, no. 5, p. 145, Dec. 2009.
  5. J. Chen, L. Yuan, and C. -K. Tang, "Robust dual motion deblurring," in Proc. CVPR, 2008.
  6. L. Yuan, J. Sun, L. Quan, and H, Y, Shum, "Image deblurring with blurred/noisy image pair," ACM Trans. Graphics, vol. 26, no. 3, July 2007.
  7. M. Ben-Ezra and S. K. Nayar. "Motion-based motion deblurring," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 6, pp. 689-698, June 2004. https://doi.org/10.1109/TPAMI.2004.1
  8. A. Agrawal, Y. Xu, and R. Raskar, "Invertibe motion blur in video," ACM Trans. Graphics, vol.28, no.3, p.95, August 2009.
  9. H. Takeda and P. Milanfar, "Removing motion blur with space-time processing," IEEE Trans. Image Process., vol. 20, no. 10, pp. 2990-3000, October 2011. https://doi.org/10.1109/TIP.2011.2131666
  10. Y. Wang and W. Yin, "Compresses sensing via iterative support detection," CAAM Technical Report TR09-30, 2009.
  11. N. Otsu, "A threshold selection method from gray level histogram," IEEE Trans. Syst. Man Cyber,, vol. 9, pp. 62-66, Jan. 1979. https://doi.org/10.1109/TSMC.1979.4310076
  12. F. Crete, T. Dolmiere, P. Ladret, and M. Nicolas, "The blur effect: perceptual and estimation with a new no-reference perceptual blur metric," in Proc. SPIE Electronic Imaging, 2007.