Skip to main content

Luminance-Hue Specification in the RGB Space

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9087))

Abstract

This paper is concerned with a problem arising when editing color images, namely the Luminance-Hue Specification. This problem often occurs when converting an edited image in a given color-space to RGB. Indeed, the colors often get out of the standard range of the RGB space which is commonly used by most of display hardwares. Simple truncations lead to inconsistency in the hue and luminance of the edited image. We formalize and describe this problem from a geometrical point of view. A fast algorithm to solve the considered problem is given. We next focus on its application to image colorization in the RGB color space while most of the methods use other ones. Using directly the three RGB channels, our model avoids artifact effects which appear with other color spaces. Finally a variational model that regularizes color images while dealing with Luminance Hue Specification problem is proposed.

This study has been carried out with financial support from the French State, managed by the French National Research Agency (ANR) in the frame of the Investments for the future Programme IdEx Bordeaux (ANR-10-IDEX-03-02). J-F. Aujol is a member of Institut Universitaire de France.

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

Buying options

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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Barnes, C., Shechtman, E., Finkelstein, A., Goldman, D.: Patchmatch: a randomized correspondence algorithm for structural image editing. ACM Transactions on Graphics 28(3), 24 (2009)

    Article  Google Scholar 

  2. Beck, A., Teboulle, M.: A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM Journal on Mathematical Analysis 2(1), 183–202 (2009)

    MATH  MathSciNet  Google Scholar 

  3. Bresson, X., Chan, T.F.: Fast dual minimization of the vectorial total variation norm and applications to color image processing. Inverse Problems and Imaging 2(4), 455–484 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  4. Bugeau, A., Ta, V.T., Papadakis, N.: Variational exemplar-based image colorization. IEEE Transactions on Image Processing 23(1), 298–307 (2014)

    Article  MathSciNet  Google Scholar 

  5. Chambolle, A., Pock, T.: A first-order primal-dual algorithm for convex problems with applications to imaging. Journal of Mathematical Imaging and Vision 40(1), 120–145 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  6. Chien, C.L., Tseng, D.C.: Color image enhancement with exact hsi color model. international journal of innovative computing, information and control 7(12), 6691–6710 (2011)

    Google Scholar 

  7. Fitschen, J.H., Nikolova, M., Pierre, F., Steidl, G.: A variational model for color assignment. In: SSVM, pp. 1–12 (to appear 2015)

    Google Scholar 

  8. Gonzales, R.C., Woods, R.E.: Digital image processing. Addison-Wesley Publishing Company (1993)

    Google Scholar 

  9. Horiuchi, T.: Colorization algorithm using probabilistic relaxation. Image and Vision Computing 22(3), 197–202 (2004)

    Article  Google Scholar 

  10. Irony, R., Cohen-Or, D., Lischinski, D.: Colorization by example. In: Eurographics Conference on Rendering Techniques, pp. 201–210. Eurographics Association (2005)

    Google Scholar 

  11. Levin, A., Lischinski, D., Weiss, Y.: Colorization using optimization. ACM Transactions on Graphics 23(3), 689–694 (2004)

    Article  Google Scholar 

  12. Nikolova, M., Steidl, G.: Fast hue and range preserving histogram specification: Theory and new algorithms for color image enhancement. IEEE Transactions on Image Processing 23(9), 4087–4100 (2014)

    Article  MathSciNet  Google Scholar 

  13. Pierre, F., Aujol, J.F., Bugeau, A., Papadakis, N., Ta, V.T.: Exemplar-based colorization in RGB color space. IEEE International Conference on Image Processing (2014)

    Google Scholar 

  14. Pierre, F., Aujol, J.F., Bugeau, A., Papadakis, N., Ta, V.T.: Luminance-chrominance model for image colorization. SIAM Journal on Imaging Sciences (to appear). https://hal.archives-ouvertes.fr/hal-01051308

  15. Quang, M.H., Kang, S.H., Le, T.M.: Image and video colorization using vector-valued reproducing kernel hilbert spaces. Journal of Mathematical Imaging and Vision 37(1), 49–65 (2010)

    Article  MathSciNet  Google Scholar 

  16. Rudin, L.I., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algorithms. Physica D: Nonlinear Phenomena 60(1), 259–268 (1992)

    Article  MATH  Google Scholar 

  17. Takahama, T., Horiuchi, T., Kotera, H.: Improvement on colorization accuracy by partitioning algorithm in cielab color space. In: Aizawa, K., Nakamura, Y., Satoh, S. (eds.) PCM 2004. LNCS, vol. 3332, pp. 794–801. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  18. Welsh, T., Ashikhmin, M., Mueller, K.: Transferring color to greyscale images. ACM Transactions on Graphics 21(3), 277–280 (2002)

    Article  Google Scholar 

  19. Williams, A., Barrus, S., Morley, R.K., Shirley, P.: An efficient and robust ray-box intersection algorithm. In: ACM SIGGRAPH 2005 Courses, p. 9 (2005)

    Google Scholar 

  20. Yoshinari, K., Hoshi, Y., Taguchi, A.: Color image enhancement in hsi color space without gamut problem. In: 6th International Symposium on Communications, Control and Signal Processing (ISCCSP), pp. 578–581. IEEE (2014)

    Google Scholar 

  21. Yoshinari, K., Murahira, K., Hoshi, Y., Taguchi, A.: Color image enhancement in improved hsi color space. In: International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS), 2013, pp. 429–434. IEEE (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Fabien Pierre .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Pierre, F., Aujol, JF., Bugeau, A., Ta, VT. (2015). Luminance-Hue Specification in the RGB Space. In: Aujol, JF., Nikolova, M., Papadakis, N. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2015. Lecture Notes in Computer Science(), vol 9087. Springer, Cham. https://doi.org/10.1007/978-3-319-18461-6_33

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-18461-6_33

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18460-9

  • Online ISBN: 978-3-319-18461-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics