Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Hybrid Super-Resolution Algorithm Robust to Cut-Change

컷 전환에 적응적인 혼합형 초고해상도 기법

  • Kwon, Soon-Chan (Department of Electronic Engineering, Kwangwoon University) ;
  • Lim, Jong-Myeong (Department of Electronic Engineering, Kwangwoon University) ;
  • Yoo, Jisang (Department of Electronic Engineering, Kwangwoon University)
  • Received : 2013.02.07
  • Accepted : 2013.03.12
  • Published : 2013.07.31
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Abstract

In this paper, we propose a hybrid super-resolution algorithm robust to cut-change. Existing single-frame based super-resolution algorithms are usually fast, but quantity of information for interpolation is limited. Although the existing multi-frame based super-resolution algorithms generally robust to this problem, the performance of algorithm strongly depends on motions of input video. Furthemore at boundary of cut, applying of the algorithm is limited. In the proposed method, we detect a define boundary of cut using cut-detection algorithm. Then we adaptively apply a single-frame based super-resolution method to detected cut. Additionally, we propose algorithms of normalizing motion vector and analyzing pattern of edge to solve various problems of existing super-resolution algorithms. The experimental results show that the proposed algorithm has better performance than other conventional interpolation methods.

본 논문에서는 이산 웨이블릿 변환(discrete wavelet transform: DWT)을 이용한 단일영상 기반의 초고해상도 기법(super-resolution)과, 복수영상 기반의 초고해상도 기법을 제시하고 두 기법을 혼합한 새로운 초고해상도 기법 기법을 제안한다. 기존의 단일 영상 기반의 초고해상도 기법의 경우 처리 시간이 빠르다는 장점이 있으나 영상 보간 시 사용할 수 있는 정보량이 제한적이다. 또한 기존 복수영상 기반의 초고해상도 기법은 단일 영상을 사용했을 경우보다 영상의 보간 시 많은 정보를 사용할 수 있으나 영상의 내용에 따라 기법의 적용이 제한적이고, 컷(cut)의 경계 부근에서 기법의 성능이 매우 떨어지는 단점이 있다. 제안된 기법에서는 컷 검출(cut-detection) 기법을 통해 각 장면의 경계부근에서 적응적으로 단일영상 기반의 초고해상도 기법을 사용한다. 또한 움직임 벡터의 정규화 및 블록 단위의 윤곽선(edge) 패턴 분석을 통해 여러 제한조건에 강한 복수 영상 기반의 초고해상도 기법을 제안한다. 실험을 통하여 제안된 기법이 객관적, 주관적으로 기존의 기법보다 우수한 성능을 보이는 것을 확인하였다.

Keywords

References

  1. S. C. Kwon and J. Yoo, "Super resolution algorithm by motion estimation with sub-pixel accuracy using 6-tap FIR filter," KICS Journals, vol. 37, no. 6, pp. 464-472, June 2012. https://doi.org/10.7840/KICS.2012.37.6A.464
  2. J. M. Lim and J. Yoo, "Super-resolution algorithm using discrete wavelet transform for single-image," KOSBE Journals, vol. 17, no. 2, pp. 344-353, Mar. 2012. https://doi.org/10.5909/JEB.2012.17.2.344
  3. S. C. Park, M. K. Park, and M. G. Kang, "Super- resolution image reconstruction: a technical overview," IEEE Signal Processing Magazine, vol. 20, no. 3, pp. 21-36, May 2003. https://doi.org/10.1109/MSP.2003.1203207
  4. W. T. Freeman, T. R. Jones and E. C. Pasztor, "Example-based super-resolution," IEEE Trans. Computer Graphics and Applications, vol. 22, no. 2, pp. 56-65, Mar. 2002.
  5. H. Chang, D. Y. Yeung and Y. Xiong, "Super- resolution through neighbor embedding," Conference on Computer Vision and Pattern Recognition Proceedings of the 2004, IEEE Trans. Computer Society, vol. 1, pp. 275-282, Jun. 2004.
  6. Y. M. Seong and H. W. Park, "Super resolution image reconstruction using phase correlation based subpixel registration from a sequence of frames," IEEK general conference, Seoul Univ., Korea, pp. 481-484, Nov. 2005.
  7. H. G. Ha, I. S. Jang, K. W. Ko and Y. H. Ha, "Sub-pixel shift estimation in noisy image using iterative phase correlation of a selected local region," IEEK Journals, vol. 47, no. 1, pp. 103-111, Jan. 2010.
  8. S. Farsiu and P. Milanfar,"Kernel regression for image processing and reconstruction," IEEE Trans. Image Processing, vol. 16, no. 2, pp. 349-366, Feb. 2007. https://doi.org/10.1109/TIP.2006.888330
  9. M. Elad, H. Takeda and P. Milanfar, "Generalizing the nonlocal-means to super resolution reconstruction," IEEE Trans. on Image Processing, vol. 18, no. 1, pp. 36-51, Jan. 2009. https://doi.org/10.1109/TIP.2008.2008067
  10. S. C. Jeong and Y. L. Choi, "Video super resolution algorithm using bi-directional overlapped block motion compensation and on-the-fly dictionary training," IEEE Trans. Circuits Syst. Video Technol., vol. 21, no. 3, pp. 274-285, Mar. 2011. https://doi.org/10.1109/TCSVT.2010.2087454
  11. J. N. Park, J. D. Lee and Y. Huh, "Cut detection methods of real-time image sequences using color characteristics," IEEK Journals, vol. 39, no. 2, pp. 64-74, Jan. 2002.
  12. A. L. Peter, A. Joch, J. Lainema, G. Bjontegaard and M. Karczewicz, "Adaptive de-blocking filter," IEEE Trans. Circuits Syst. Video Technol., vol. 13, no. 7, pp. 614-619, Jul. 2003. https://doi.org/10.1109/TCSVT.2003.815175
  13. Y. H. Seo, J. H. Kim, D. G. Kim, J. Yoo and D. W. Kim, "An effective method to treat the boundary pixels for image compression with DWT," KICS Journals, vol. 29, no. 6, pp. 618-627, Jun. 2002.
  14. T. H. Kim, Y. S. Moon and C. S. Han, "Estimation of real boundary with subpixel accuracy in digital imagery," KSPE Journals, vol. 16, no. 8, pp. 16-22. Aug. 1999.
  15. T. Wiegand, G. J. Sullivan, G. Bjontegaard, and A. Luthra, "Overview of the H.264/AVC Video coding standard," IEEE Trans. Circuits Syst. Video Technol., vol. 13, no. 7, pp. 560-576, Jul. 2003. https://doi.org/10.1109/TCSVT.2003.815165
  16. N. Hirai, T. Kato, T. Song and T. Shimamoto, "An efficient architecture for spiral-type motion estimation for H.264/AVC," IEEK General Conference in the Korea, Je-ju, Jul. 2009.
  17. Y. Ismail and J.B. McNeely, M. Shaaban, H. Mahmoud and M. A. Bayoumi, "Fast motion estimation system using dynamic models for H.264/AVC video coding," Trans. Circuits Syst. Video Technol., vol. 22, no. 1, pp. 28-42, Jan. 2012. https://doi.org/10.1109/TCSVT.2011.2148450
  18. H. M. Wong, O. C. Au, A. Chang, S. K. Yip and C. W. Ho, "Fast mode decision and motion estimation for H.264(FMDME)," IEEE International Symposium on Circuits and Systems ISCAS'06, Greece, May 2006.
  19. V. K. Asari, M. N. Islam and M. A. Karim, "Superresolution enhancement technique for low resolution video," IEEE Trans. Consumer Electronics, vol. 56, no. 2, pp.919-924, May 2010. https://doi.org/10.1109/TCE.2010.5506020
  20. S. Winkler, "The evolution of video quality measurement: From PSNR to hybrid metrics," IEEE Trans. Broadcasting, vol. 54, no. 3, pp.660-668, Sep. 2008. https://doi.org/10.1109/TBC.2008.2000733