Resolution Enhancement by Prediction of the High-Frequency Image Based on the Laplacian Pyramid

  • Bo-Won JeonEmail author
  • Rae-Hong Park
  • Seungjoon Yang
Open Access
Research Article
Part of the following topical collections:
  1. Super-Resolution Imaging: Analysis, Algorithms, and Applications


According to recent advances in digital image processing techniques, interest in high-quality images has been increased. This paper presents a resolution enhancement (RE) algorithm based on the pyramid structure, in which Laplacian histogram matching is utilized for high-frequency image prediction. The conventional RE algorithms yield blurring near-edge boundaries, degrading image details. In order to overcome this drawback, we estimate an HF image that is needed for RE by utilizing the characteristics of the Laplacian images, in which the normalized histogram of the Laplacian image is fitted to the Laplacian probability density function (pdf), and the parameter of the Laplacian pdf is estimated based on the Laplacian image pyramid. Also, we employ a control function to remove overshoot artifacts in reconstructed images. Experiments with several test images show the effectiveness of the proposed algorithm.


Pyramid Probability Density Function Digital Image Processing Image Processing Technique Pyramid Structure 


  1. 1.
    Park SC, Park MK, Kang MG: Super-resolution image reconstruction: a technical overview. IEEE Signal Processing Magazine 2003, 20(3):21–36. 10.1109/MSP.2003.1203207CrossRefGoogle Scholar
  2. 2.
    Jain AK: Fundamentals of Digital Image Processing. Prentice-Hall, Englewood Cliffs, NJ, USA; 1989.zbMATHGoogle Scholar
  3. 3.
    Gonzalez RC, Woods RE: Digital Image Processing. 2nd edition. Prentice-Hall, Upper Saddle River, NJ, USA; 2002.Google Scholar
  4. 4.
    Li X, Orchard MT: New edge-directed interpolation. IEEE Transactions on Image Processing 2001, 10(10):1521–1527. 10.1109/83.951537CrossRefGoogle Scholar
  5. 5.
    Biancardi A, Cinque L, Lombardi L: Improvements to image magnification. Pattern Recognition 2002, 35(3):677–687. 10.1016/S0031-3203(01)00034-6CrossRefGoogle Scholar
  6. 6.
    Leu J-G: Sharpness preserving image enlargement based on a ramp edge model. Pattern Recognition 2001, 34(10):1927–1938. 10.1016/S0031-3203(00)00117-5CrossRefGoogle Scholar
  7. 7.
    Wang Q, Ward R: A contour-preserving image interpolation method. Proc. IEEE International Conference on Image Processing (ICIP '03), September 2003, Barcelona, Spain 3: 673–676.Google Scholar
  8. 8.
    Greenspan H, Anderson CH, Akber S: Image enhancement by nonlinear extrapolation in frequency space. IEEE Transactions on Image Processing 2000, 9(6):1035–1048. 10.1109/83.846246MathSciNetCrossRefGoogle Scholar
  9. 9.
    Takahashi Y, Taguchi A: An arbitrary scale image enlargement method with the prediction of high-frequency components. Electronics and Communications in Japan (Part III: Fundamental Electronic Science) 2003, 86(8):41–51. 10.1002/ecjc.10018CrossRefGoogle Scholar
  10. 10.
    Carey WK, Chuang DB, Hemami SS: Regularity-preserving image interpolation. IEEE Transactions on Image Processing 1999, 8(9):1293–1297. 10.1109/83.784441CrossRefGoogle Scholar
  11. 11.
    Freeman WT, Jones TR, Pasztor EC: Example-based super-resolution. IEEE Computer Graphics and Applications 2002, 22(2):56–65. 10.1109/38.988747CrossRefGoogle Scholar
  12. 12.
    Sun J, Zheng N-N, Tao H, Shum H-Y: Image hallucination with primal sketch priors. Proc. IEEE International Conference on Computer Vision and Pattern Recognition (CVPR '03), June 2003, Madison, Wis, USA 2: 729–736.Google Scholar
  13. 13.
    Burt PJ, Adelson EH: The Laplacian pyramid as a compact image code. IEEE Transactions on Communications 1983, 31(4):532–540. 10.1109/TCOM.1983.1095851CrossRefGoogle Scholar
  14. 14.
    Ramponi G, Polesel A: Rational unsharp masking technique. Journal of Electronic Imaging 1998, 7(2):333–338. 10.1117/1.482649CrossRefGoogle Scholar
  15. 15.
    Cheikh FA, Gabbouj M: Directional-rational approach for color image enhancement. Proc. IEEE Int. Symp. Circuits and Systems (ISCAS '00), May 2000, Geneva, Switzerland 3: 563–566.Google Scholar

Copyright information

© Jeon et al. 2006

Authors and Affiliations

  1. 1.Department of Electronic Engineering, School of EngineeringSogang UniversitySeoulKorea
  2. 2.Digital Media Research and Development CenterSamsung Electronics Corporation, LtdSuwonKorea

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