Skip to main content
SpringerLink
Log in

An Edge-Sensing Universal Demosaicing Algorithm

  • Conference paper
Advanced Concepts for Intelligent Vision Systems (ACIVS 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6474))

Abstract

In this paper, we introduce an edge detection algorithm for mosaiced images which can be used to enhance generic demosaicing algorithms. The algorithm is based on pixels color differences in the horizontal, vertical and diagonal directions. By using our edge-detection technique to enhance the universal demosaicing algorithm of Lukac et al., experimental results show that the presence of color shifts and artefacts in demosaiced images is reduced. This is confirmed in regard to both subjective and objective evaluation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Tsai, C.Y., Song, K.Y.: A new edge-adaptive demosaicing algorithm for color filter arrays. Image and Vision Computing 25, 1495–1508 (2007)

    Article  Google Scholar 

  2. Lee, W., Lee, S., Kim, J.: Cost-effective color filter array demosaicing using spatial correlation. IEEE Transactions on Consumer Electronics 52(2), 547–554 (2006)

    Article  Google Scholar 

  3. Keys, R.G.: Cubic convolution interpolation for digital image processing. IEEE Transactions on Acoustic, Speech and Signal Processing ASSP-29, 1153–1160 (1981)

    Article  MathSciNet  MATH  Google Scholar 

  4. Cok, D.R.: Signal processing method and apparatus for producing interpolated chrominance values in a sampled color image. U.S. patent 4642768 (1987)

    Google Scholar 

  5. Adams, J.E.: Interactions between color plane interpolation and other image processing functions in electronic photography. In: Proceedings of SPIE, vol. 2416, pp. 144–151 (1995)

    Google Scholar 

  6. Chung, K.H., Chan, Y.H.: Color demosaicing using variance of color differences. IEEE Transactions on Image Processing 15(10), 2944–2955 (2006)

    Article  Google Scholar 

  7. Chang, L., Tan, Y.P.: Effective use of spatial and spectral correlations for color filter array demosaicking. IEEE Transactions on Consumer Electronics 50(1), 355–365 (2004)

    Article  Google Scholar 

  8. Kakarala, R., Baharav, Z.: Adaptive demosaicing with the principle vector method. IEEE Transactions on Consumer Electronics 48, 932–937 (2002)

    Article  Google Scholar 

  9. Li, X., Orchard, M.T.: New edge directed interpolation. IEEE Transactions on Image Processing 10(10) (2001)

    Google Scholar 

  10. Pei, S.C., Tam, I.K.: Effective color interpolation in CCD color filter arrays using signal correlation. IEEE Transactions on Circuits and Systems for video technology 13(6), 503–513 (2003)

    Article  Google Scholar 

  11. Lukac, R., Plataniotis, K.N., Hatzinakos, D.: A new CFA interpolation framework. Signal Processing 86, 1559–1579 (2006)

    Article  MATH  Google Scholar 

  12. Bayer, B.E.: Color imaging array. U.S. Patent 3971065 (1976)

    Google Scholar 

  13. Yamanaka, S.: Solid state camera. U.S. Patent 4054906 (1977)

    Google Scholar 

  14. Lukac, R., Plataniotis, K.N.: Color filter arrays: design and performance analysis. IEEE Transactions on Consumer Electronics 51(4), 1260–1267 (2004)

    Article  Google Scholar 

  15. FillFactory: Technology image sensor: the color filter array, http://web.archive.org/web/20051219223659/www.fillfactory.com/htm/technology/htm/rgbfaq.htm

  16. Parmar, M., Reeves, S.J.: A perceptually based design methodology for color filter arrays. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), vol. 3, pp. 473–476 (2004)

    Google Scholar 

  17. Hirakawa, H., Wolfe, P.J.: Spatio-spectral color filter array design for optimal image recovery. IEEE Transactions on Image Processing 17(2), 1876–1890 (2008)

    Article  MathSciNet  Google Scholar 

  18. Lukac, R., Plataniotis, K.N.: Universal demosaicking for imaging pipelines with an RGB color filter array. Pattern Recognition 38, 2208–2212 (2005)

    Article  Google Scholar 

  19. Gunturk, B.K., Glotzbach, J., Altunbasak, Y., Schaffer, R.W., Murserau, R.M.: Demosaicking: color filter array interpolation. IEEE Signal Processing Magazine 22(1), 44–54 (2005)

    Article  Google Scholar 

  20. Lukac, R., Plataniotis, K.N.: Data adaptive filters for demosaicking: a framework. IEEE Transactions on Consumer Electronics 51(2), 560–570 (2005)

    Article  Google Scholar 

  21. Lukac, R., Plataniotis, K.N.: A robust, cost-effective postprocessor for enhancing demosaicked camera images. Real-Time Imaging 11(2), 139–150 (2005)

    Article  Google Scholar 

  22. Li, X.: Demosaicing by successive approximations. IEEE Transactions on Image Processing 14(3), 370–379 (2005)

    Article  Google Scholar 

  23. Ramanath, R., Snyder, W.E., Bilbro, G.L., Sander III, W.A.: Demosaicking methods for Bayer color arrays. Journal of Electronic Imaging 11(3), 306–315 (2002)

    Article  Google Scholar 

  24. Su, C.Y.: Highly effective iterative demosaicing using weighted-edge and color-difference interpolations. IEEE Transactions on Consumer Electronics 52(2), 639–645 (2006)

    Article  Google Scholar 

  25. Drewniok, C.: Multi-spectral edge detection: some experiments on data from Landsat-TM. International Journal of Remote Sensing 15(18), 3743–3765 (1994)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. MOIVRE, Département d’Informatique, Université de Sherbrooke, 2500 Boulevard de l’Université, Sherbrooke, Québec, Canada, J1K 2R1

    Alain Horé & Djemel Ziou

Authors
  1. Alain Horé
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Djemel Ziou
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. DGA/D4S/MRIS, CEP/GIP, 16 bis avenue Prieur de la côte d’or, 94114, Arcueil, France

    Jacques Blanc-Talon

  2. Canon Information Systems Research Australia, Sydney, Australia

    Don Bone

  3. Telecommunications and Information processing (TELIN), Ghent University, St.-Pietersnieuwstraat 41, B9000, Ghent, Belgium

    Wilfried Philips

  4. CSIRO ICT Centre, ICT Centre, Po Box 76, NSW 1710, Epping, Sydney, Australia

    Dan Popescu

  5. Physics, University of Antwerp, Universiteitsplein 1; Building N. 2610, Wilrijk, Belgium

    Paul Scheunders

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Horé, A., Ziou, D. (2010). An Edge-Sensing Universal Demosaicing Algorithm. In: Blanc-Talon, J., Bone, D., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2010. Lecture Notes in Computer Science, vol 6474. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17688-3_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-17688-3_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17687-6

  • Online ISBN: 978-3-642-17688-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation