Journal of Computer Science and Technology

, Volume 18, Issue 6, pp 822–832 | Cite as

A super-resolution method with EWA

  • Jiang ZhongDing 
  • Lin Hai 
  • Bao HuJun 
  • Ma LiZhuang 


This paper introduces a practical algorithm for super-resolution, the process of reconstructing a high-resolution image from low-resolution input ones. The emphasis of the work is to super-resolve frames from real-world image/video sequences which may contain significant object occlusion or scene changes. As the quality of super-resolved images highly relies on the correctness of image alignment between consecutive frames, the robust optical flow method is used to accurately estimate motion between the image pair. An efficient and reliable scheme is devised to detect and discard incorrect matchings which may degrade the output quality. The usage of elliptical weighted average (EWA) filter is also introduced to model the point spread function (PSF) of acquisition system in order to improve accuracy of the model. A number of complex video sequences are tested to demonstrate the applicability and reliability of the proposed algorithm.


super-resolution EWA filter image-based rendering 


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  1. [1]
    Borman S, Stevenson R. Spatial resolution enhancement of low-resolution image sequences: A comprehensive review with directions for future research. Technical Report, University of Notre Dame, 1998.Google Scholar
  2. [2]
    Tsai R, Huang T. Multiframe image restoration and registration. InAdvances in Computer Vision and Image Processing, 1984, 1: 317–339.Google Scholar
  3. [3]
    Tekalp A, Ozkan M, Sezan M. High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration. InProc. ICASSP’92. San Francisco, California, USA, Mar. 23–26, 1992, 3: 169–172.Google Scholar
  4. [4]
    Irani M, Peleg S. Improving Resolution by Image Registration.Journal of Computer Vision, Graphics, and Image Processing, 1991, 53(3): 231–239.Google Scholar
  5. [5]
    Irani M, Peleg S. Motion analysis for image enhancement: Resolution, occlusion, and transparency.Journal of Visual Communication and Image Representation 1993, 4(4): 324–335.CrossRefGoogle Scholar
  6. [6]
    Elad M, Feuer A. Restoration of single super-resolution image from several blurred, noisy and down-sampled measured images.IEEE Trans. Image. Processing, 1997, 6(2): 1646–1658.CrossRefGoogle Scholar
  7. [7]
    Patti A, Sezan M, Tekalp A. Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time.IEEE Trans. Image Processing, 1997, 6(8): 1064–1076.CrossRefGoogle Scholar
  8. [8]
    Schultz R, Stevenson R. Extraction of high-resolution frames from video sequences.IEEE Trans. Image Processing, 1996, 5(6): 996–1011.CrossRefGoogle Scholar
  9. [9]
    Hardie R, Barnard K, Armstrong E. Joint MAP registration and high-resolution image estimation using a sequence of undersampled images.IEEE Trans Image Processing, 1997, 6(12): 1621–1633.CrossRefGoogle Scholar
  10. [10]
    Capel D, Zisserman A. Super-resolution enhancement of text image sequence. InProc. ICPR’2000, Barcelona, Spain, Sept. 3–8, 2000, 1: 885–891.Google Scholar
  11. [11]
    Elad M, Feuer A. Super-resolution reconstruction of image sequences.IEEE Trans. Pattern Analysis and Machine Intelligence, 1999, 21(9): 817–834.CrossRefGoogle Scholar
  12. [12]
    Shechtman E, Caspi Y, Irani M. Increasing space-time resolution in video. InProc. ECCV’2002, Copenhagen, Denmark, May 27–June 2, 2002, 1: 753–768.Google Scholar
  13. [13]
    Lin Z, Shum H. On the fundamental limits of reconstruction-based super-resolution algorithms. InProc. CVPR’2001, Hawaii, USA, Dec. 11–13, 2001, 1: 1171–1176.Google Scholar
  14. [14]
    Eren P, Sezan M, Tekalp A. Robust, object-based high-resolution image reconstruction from low-resolution video.IEEE Trans. Image Processing, 1997, 6(10): 1446–1451.CrossRefGoogle Scholar
  15. [15]
    Zomet A, Rav-Acha A, Peleg S. Robust Superresolution. InProc. CVPR’2001, Hawaii, USA, Dec. 11–13, 2001, 1: 645–650.Google Scholar
  16. [16]
    Zhao W, Sawhney H. Is super-resolution with optical flow feasible? InProc. ECCV’2002, Copenhagen, Denmark, May 27–June 2, 2002, 2002, 1: 599–613.Google Scholar
  17. [17]
    Liu C, Shum H, Zhang C. A two-step approach to hallucinating faces: Global parametric model and local nonparametric model. InProc. CVPR’2001, Hawaii, USA, Dec. 11–13, 1: 192–198.Google Scholar
  18. [18]
    Baker S, Kanade T. Limits on super-resolution and how to break them.IEEE Trans. Pattern Analysis and Machine Intelligence, 2002, 24(9): 1167–1183.CrossRefGoogle Scholar
  19. [19]
    Hertzmann A, Jacobs C, Oliver Net al. Image analogies. InProc. SIGGRAPH’2001, Los Angeles, California, USA, August 12–17, 2001, pp.327–340.Google Scholar
  20. [20]
    Freeman W, Jones T, Pasztor E. Example-based super-resolution.IEEE Computer Graphics and Applications, 2002, 22(2): 56–65.CrossRefGoogle Scholar
  21. [21]
    Papoulis A. Generalized sampling expansion.IEEE Trans. Circuits and Systems, 1977, 24(11): 652–654.MATHCrossRefMathSciNetGoogle Scholar
  22. [22]
    Yen L. On-nonuniform sampling of bandwidth-limited signals.IRE Trans. Circuits Theory, 1956, 3(4): 251–257.MathSciNetGoogle Scholar
  23. [23]
    Horn B. Robot Vision. MIT Press, 1986.Google Scholar
  24. [24]
    Barron J, Fleet D, Beauchemin S. Performance of optical flow.International Journal of Computer Vision, 1994, 12(1): 43–77.CrossRefGoogle Scholar
  25. [25]
    Black M, Anandan P. The robust estimation of multiple motions: Parametric and piecewise-smooth flow fields.Journal of Computer Vision and Image Understanding, 1996, 63(1): 75–104.CrossRefGoogle Scholar
  26. [26]
    Black M, Fleet D, Yacoob Y. Robustly estimating changes in image appearance.Journal of Computer Vision and Image Understanding, 2000, 78(1): 8–31.CrossRefGoogle Scholar
  27. [27]
    Greene N, Heckbert P. Creating raster ominimax images from multiple perspective views using the elliptical weighted average filter.IEEE Computer Graphics and Applications, 1986, 6(6): 21–27.CrossRefGoogle Scholar
  28. [28]
    Heckbert P. Fundamentals of texture mapping and image warping [Thesis]. Department of Electrical Engineering and Computer Science, University of Califorrnia at Berkeley, June 17, 1989.Google Scholar
  29. [29]
    Zwicker M, Pfister H, Baar J, Gross M. Surface splatting. InProc SIGGRAPH’2001, Los Angeles, California, USA, August 12–17, 2001, pp.371–378.Google Scholar
  30. [30]
    Ren L, Pfister H, Zwicker M. Object space EWA surface splatting: A hardware accelerated approach to high quality point rendering.Computer Graphics Forum, 2002, 21(3): 461–470.CrossRefGoogle Scholar
  31. [31]
    Zwicker M, Pfister H, Baar J, Gross M. EWA volume splatting. InProc. IEEE Visualization’2001, San Diego, CA, USA Oct. 24–26, 2001, pp.29–36.Google Scholar
  32. [32]
    Sawhney H, Guo Y, Hanna Ket al. Hybrid sterco camera: An IBR approach for synthesis of very high resolution stereoscopic image sequences. InProc. SIGGRAPH’2001, Los Angeles, California, USA, August 12–17, 2001, pp.451–460.Google Scholar
  33. [33]
    Westover L. Footprint evaluation for volume rendering. InProc. SIGGRAPH’90, Dallas, Texas, USA, Sept. 1990, pp.367–376.Google Scholar
  34. [34]
    Brown L. A survey of image registration techniques.ACM Computing Surveys, 1992, 24(4): 325–376.CrossRefGoogle Scholar
  35. [35]
    Schreiber W. Fundamentals of Electronic Imaging Systems. Springer-Verlag, 1986.Google Scholar
  36. [36]
    Altunbasak Y, Patti A, Mersereau R. Super-resolution still and video reconstruction from MPEG-coded video.IEEE Trans. Circuits and Systems for Video Technology, 2002, 12(4): 217–226.CrossRefGoogle Scholar

Copyright information

© Science Press, Beijing China and Allerton Press Inc. 2003

Authors and Affiliations

  • Jiang ZhongDing 
    • 1
  • Lin Hai 
    • 1
  • Bao HuJun 
    • 1
  • Ma LiZhuang 
    • 2
  1. 1.State Key Laboratory of CAD and CGZhejiang UniversityHangzhouP.R. China
  2. 2.Department of Computer Science and EngineeringShanghai Jiaotong UniversityShanghaiP.R. China

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