Improvement of Conventional Deinterlacing Methods with Extrema Detection and Interpolation

  • Jérôme Roussel
  • Pascal Bertolino
  • Marina Nicolas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4179)


This article presents a new algorithm for spatial deinterlacing that could easily be integrated in a more complete deinterlacing system, typically a spatio-temporal motion adaptive one. The spatial interpolation part often fails to reconstruct close to horizontal lines with a proper continuity, leading to highly visible artifacts. Our system preserves the structure continuity taking into account that the mis-interpolated points usually correspond to local value extrema. The processing is based on chained lists and connected graph construction. The new interpolation method is restricted to such structures, for the rest of the image, a proper traditional directional spatial interpolation gives satisfactory results already. Although the number of pixels affected by the extrema interpolation is relatively small, the overall image quality is subjectively well improved. Moreover, our solution allows to gain back one of the major advantages of motion compensation methods, without having to afford their complexity cost.


Motion Compensation Spatial Interpolation Consumer Electronics Table Tennis Edge Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Sugiyama, K., Nakamura, H.: A method of de-interlacing with motion compensated interpolation. IEEE Trans. on Consumer Electronics 45, 611–616 (1999)CrossRefGoogle Scholar
  2. 2.
    Koivunen, T.: Motion detection of an interlaced video signal. IEEE Trans. on Consumer Electronics 40, 753–760 (1994)CrossRefGoogle Scholar
  3. 3.
    Lin, S.F., Chang, Y.L., Chen, L.G.: Motion adaptive interpolation with horizontal motion detection for deinterlacing. IEEE Trans. on Consumer Electronics 49, 1256–1265 (2003)CrossRefGoogle Scholar
  4. 4.
    de Haan, G., Bellers, E.: Deinterlacing - an overview. Proceedings of the IEEE 86, 1839–1857 (1998)CrossRefGoogle Scholar
  5. 5.
    Doyle, T.: Interlaced to sequential conversion for EDTV applications. In: Proc. 2nd International Workshop Signal Processing of HDTV, pp. 412–430 (1988)Google Scholar
  6. 6.
    Chen, T., Wu, H.R., Yu, Z.H.: Efficient deinterlacing algorithm using edge-based line average interpolation. Optical Engineering 39, 2101–2105 (2000)CrossRefGoogle Scholar
  7. 7.
    Yoo, H., Jeong, J.: Direction-oriented interpolation and its application to de-interlacing. IEEE Trans. on Consumer Electronics 48, 954–962 (2002)Google Scholar
  8. 8.
    Park, M.K., Kang, M.G., Nam, K., Oh, S.G.: New edge depent deinterlacing algorithm based on horizontal edge pattern. IEEE Trans. on Consumer Electronics 49, 1508–1512 (2003)CrossRefGoogle Scholar
  9. 9.
    Byun, M., Park, M.K., Kang, M.G.: Edi-based deinterlacing using edge patterns. In: IEEE International Conference on Image Processing, vol. 2, pp. 1018–1021 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jérôme Roussel
    • 1
    • 2
  • Pascal Bertolino
    • 2
  • Marina Nicolas
    • 1
  1. 1.ST Microelectronics S.A.GrenobleFrance
  2. 2.Laboratory of Images and SignalsINPGSt Martin d’HèresFrance

Personalised recommendations