ARPS 움직임 추정과 POCS 복원을 동시에 이용하는 HR 영상 재구성

Reconstruction of High Resolution Images by ARPS Motion Estimation and POCS Restoration

  • 송희근 (서울시립대학교 전자전기컴퓨터공학부 컴퓨터비전연구실) ;
  • 김용철 (서울시립대학교 전자전기컴퓨터공학부 컴퓨터비전연구실)
  • 발행 : 2009.03.31

초록

POCS (projection onto convex sets)를 이용하는 고해상도 영상 재구성에서는 재구성 연산 사이에 프레임간 움직임을 추정함으로써 양질의 HR (high resolution) 영상을 얻을 수 있으나, 반복적인 움직임 추정으로 인해 연산량은 증가한다. 본 논문에서는 기존의 ARPS (adaptive rood pattern search) 움직임 추정법을 수정하여 연산량을 줄이면서, 움직임 추정과 POCS 복원을 동시에 수행하는 HR 영상의 재구성 알고리즘을 제안한다. ARPS에서 필요한 기준 움직임의 값으로 POCS 복원의 이전 단계에서 추정한 움직임 벡터의 값과 위상 상관도법으로 얻은 값을 이용하여 연산량을 줄였다. 또한, 추정된 움직임을 정규화하여 그 정확도를 더욱 향상시켰다. 실험 결과, 전체탐색 블록 정합법과 POCS를 동시에 수행하여 영상을 재구성한 경우와 비교했을 때 유사한 화질의 HR 영상을 약 30배 빠르게 재구성하였다.

In POCS (projection onto convex sets)-based reconstruction of HR (high resolution) image, the quality of reconstructed image is gradually improved through iterative motion estimation and image restoration. The amount of computation, however, increases because of the repeated inter-frame motion estimation. In this paper, an HR reconstruction algorithm is proposed where modified ARPS (adaptive rood pattern search) and POCS are simultaneously performed. In the modified ARPS, the motion estimates obtained from phase correlation or from the previous steps in POCS restoration are utilized as the initial reference in the motion estimation. Moreover, estimated motion is regularized with reference to the neighboring blocks' motion to enhance the reliability. Computer simulation results show that, when compared to conventional methods which are composed of full search block matching and POCS restoration, the proposed method is about 30 times faster and yet produces HR images of almost equal or better quality.

키워드

참고문헌

  1. S. Park, M. Park, and M. Kang, 'Super-resolution image reconstruction: A technical overview,' IEEE Signal Processing Magazine, pp. 21-36, May, 2003 https://doi.org/10.1109/MSP.2003.1203207
  2. S. Borman and R. Stevenson, 'Spatial resolution enhancement of low-resolution image sequences. A Comprehensive review with directions for future research,' Image and Signal Analysis, University of Notre Dame, Tech. Rep., 1998
  3. S. Kim, N. Bose, and H. Valenzuela, 'Recursive reconstruction of high resolution image from noisy undersampled multiframes,' IEEE Trans. on Acoustics, Speech and Signal Proc., Vol.38, No.6. pp.1013-1027, June, 1990 https://doi.org/10.1109/29.56062
  4. S. Rhee and M. Kang, 'DCT-based regularized algorithm for high-resolution image reconstruction', IEEE Proceedings of ICIP, Vol. 3, pp.184-187, 1999 https://doi.org/10.1109/ICIP.1999.817096
  5. J. Mateos, A Katsaggelos, and R. Molina, 'Simultaneous motion estimation and resolution enhancement of compressed low resolution video,' IEEE Proceedings of ICIP, Vol. 2, p.653-656, 2000 https://doi.org/10.1109/ICIP.2000.899793
  6. R. Hardi, K. Barnard, and E. Armstrong, 'Joint MAP registration and high-resolution image estimation using a sequence of undersampled images', IEEE Trans. on Image Processing, Vol.6, No.12, pp. 1621-1633, Dec. 1997 https://doi.org/10.1109/83.650116
  7. S. Park, M. Kang, C. Segall, and A. Katsaggelos, 'Spatially adaptive high-resolution image reconstruction of DCT-based compressed images,' IEEE Trans. on Image Processing, Vol. 13, pp.573-585, Apr. 2004 https://doi.org/10.1109/TIP.2003.819233
  8. R. Schultz and R. Stevenson, 'Extraction of high-resolution frames from video sequences,' IEEE Trans. on Image Processing, Vol.5, No.6, pp.996-1011, Jun. 1996 https://doi.org/10.1109/83.503915
  9. R. Schultz and R. Stevenson, 'Bayesian estimation of subpixel-resolution motion fields and high-resolution video stills,' IEEE Proceedings of ICIP, Vol. 3, p.62,1997 https://doi.org/10.1109/ICIP.1997.631981
  10. A. Patti, M. Sezan, and A. Tekalp, 'Super resolution video reconstruction with arbitrary sampling lattices and non-zero aperture time,' IEEE Trans. on Image Processing, Vol.6, No.8, pp.1064-1076, 1997 https://doi.org/10.1109/83.605404
  11. H. Stark and P. Oskoui, 'High-resolution image recovery from image-plane arrays, using convex projections,' J. Opt. Soc. Amer. A, Vol. 6, No. 11, Nov. 1989
  12. A. Tekalp, M. Ozkan, and M. Sezan, 'High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration', IEEE Proceedings of ICASSP, Vol. 3, pp. 169-172. Mar. 1992
  13. Y. Altunbasak, A Patti, and R. Mersereau, 'Super-resolution still and video reconstruction from MPEG-coded video', IEEE Trans. on Circuits and Systems for Video Tech., Vol. 12, No. 4, 2002
  14. 최종범, 오태석, 김용철, '정규화된 블록매칭과 POCS에 의한 HR 영상 재구성', 한국통신학회 논문지, Vol. 30. No. 8C, pp. 824-831, 2005
  15. R. Gonzalez and R. Woods, Digital image processing 2'nd Eds., Prentice Hall, 2002
  16. Y. Nie and K. Ma, "Adaptive rood pattern search for fast block-matching motion estimation", IEEE Trans. on Image Processing, Vol. 11, No. 12, Dec. 2002
  17. P. Vandewalle, L. Sbaiz, S. SÜsstrunk, and M. Vetterli, 'Registration of aliased images for super-resolution imaging,' Proc. SPIE/IS&T Visual Communications and Image Processing Conference, Vol. 6077, pp. 13-23, 2006 https://doi.org/10.1117/12.644032
  18. S. Farsiu, D. Robinson, and P.Milanfar, 'MDSP resolution enhancement software,' [Online]. Available: http://www.soe.ucsc.edu/~milanfar/software/sr-datasets.html, 2004