Advertisement

An Efficient Approach to Restore Naturalness of Non-uniform Illumination Images

  • Utkarsh GoelEmail author
  • Bhupendra Gupta
  • Mayank Tiwari
Short Paper
  • 52 Downloads

Abstract

Enhancement of the image details without affecting the naturalness is a difficult task, especially for non-uniformly illuminated images. While dealing with non-uniformly illuminated images, most of the available image enhancement approaches show common drawbacks such as loss of naturalness and appearance of artifacts in the resultant image. It is very difficult to maintain a trade-off between detail enhancement and naturalness. To deal with this problem, we propose an efficient approach for enhancing local details as well as the color information and preserve the naturalness in the resultant image. The proposed method is effectively enhancing the local details, along with the visibility of the image (having dark and bright regions) without affecting the naturalness. Experimental results also support our claims and confirmations that the proposed approach outperforms other state-of-the-art methods.

Keywords

Image enhancement Naturalness preservation Contrast enhancement Color preservation 

Notes

Acknowledgements

We are very grateful to the all the reviewers for giving their precious time in order to review our work. We have found their suggestion very useful in improving the quality of this research article and have humbly incorporated all their suggestions.

References

  1. 1.
    T. Arici, S. Dikbas, Y. Altunbasak, A histogram modification framework and its application for image contrast enhancement. IEEE Trans. Image Process. 18(9), 1921–1935 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
  2. 2.
    S. Chen, A. Beghdadi, Natural enhancement of color image. EURASIP J. Image Video Process. 2010(2), 1–19 (2010)CrossRefGoogle Scholar
  3. 3.
    S. Chen, A. Beghdadi, Natural rendering of color image based on retinex. in Proceedings on IEEE International Conference on Image Processing, Cairo, 1813–1816 November 2009Google Scholar
  4. 4.
    S.D. Chen, R. Ramli, Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation. IEEE Trans. Consum. Electron. 49(4), 1301–1309 (2003)CrossRefGoogle Scholar
  5. 5.
    S.-D. Chen, R. Ramli, Minimum mean brightness error bi-histogram equalization in contrast enhancement. IEEE Trans. Consum. Electron. 49(4), 1310–1319 (2003)CrossRefGoogle Scholar
  6. 6.
    D. Coltuc, P. Bolon, J. Chassery, Exact histogram specification. IEEE Trans. Image Process. 15(5), 1143–1152 (2006)CrossRefGoogle Scholar
  7. 7.
    G. Deng, A generalized unsharp masking algorithm. IEEE Trans. Image Process. 20(5), 1249–1261 (2011)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    R.C. Gonzalez, R.E. Woods, Digital Image Processing, 3rd edn. (Pearson Prentice-hall, Englewood Cliffs, 2009)Google Scholar
  9. 9.
    G. Guarnieri, S. Marsi, G. Ramponi, High dynamic range image display with halo and clipping prevention. IEEE Trans. Image Process. 20(5), 1351–1362 (2011)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    B. Gupta, T.K. Agarwal, Linearly quantile separated weighted dynamic histogram equalization for contrast enhancement. Comput. Electr. Eng. (2017) .  https://doi.org/10.1016/j.compeleceng.2017.01.010
  11. 11.
    B. Gupta, M. Tiwari, Minimum mean brightness error contrast enhancement of color images using adaptive gamma correction with color preserving framework. Int. J. Light Electron Opt. 127, 1671–1676 (2015)CrossRefGoogle Scholar
  12. 12.
    H. Ibrahim, N. Kong, Brightness preserving dynamic histogram equalization for image contrast enhancement. IEEE Trans. Consum. Electron. 53(4), 1752–1758 (2007)CrossRefGoogle Scholar
  13. 13.
    D.J. Jobson, Z. Rahman, G.A. Wodell, A multiscale retinex for bridging the gap between color images and the human observation of scenes. IEEE Trans. Image Process. 6(7), 965–976 (1997)CrossRefGoogle Scholar
  14. 14.
    D.J. Jobson, Z. Rahman, G.A. Wodell, Properties and performance of a center/surround retinex. IEEE Trans. Image Process. 6(3), 451–462 (1997)CrossRefGoogle Scholar
  15. 15.
    Z. Karel, Contrast Limited Adaptive Histogram Equalization (Academic Press Professional, New York, 1998), pp. 474–485Google Scholar
  16. 16.
    Y.T. Kim, Contrast enhancement using brightness preserving bi-histogram equalization. IEEE Trans. Consum. Electron. 43(1), 1–8 (1997)CrossRefGoogle Scholar
  17. 17.
    R. Kimmel, M. Elad, D. Shaked, R. Keshet, I. Sobel, A variational framework for retinex. Int. J. Comput. Vis. 52(1), 7–23 (2003)CrossRefzbMATHGoogle Scholar
  18. 18.
    E.W. Land, J.J. McMann, Lightness and retinex theory. J. Opt. Soc. Am. 61(1), 1–11 (1971)CrossRefGoogle Scholar
  19. 19.
    B. Li, S. Wang, Y. Geng, Image enhancement based on retinex and lightness decomposition. in Proceedings of IEEE International Conference on Image Processing, Blussels, 3417–3420 September 2011Google Scholar
  20. 20.
    M. Luo, G. Cui, B. Rigg, The development of the CIE 2000 colour-difference formula: CIEDE2000. Color Res. Appl. 26, 340–350 (2001)CrossRefGoogle Scholar
  21. 21.
    L. Meylan, Tone mapping for high dynamic range images. Ph.D thesis, EPFL (2006)Google Scholar
  22. 22.
    L. Meylan, S. Ssstrunk, High dynamic range image rendering with a retinex-based adaptive filter. IEEE Trans. Instrum. Meas. 15(9), 2820–2830 (2006)Google Scholar
  23. 23.
    S. Poddar, S. Tewary, D. Sharma et al., Non-parametric modified histogram equalisation for contrast enhancement. IET Image Process. 7(7), 641–652 (2013)CrossRefGoogle Scholar
  24. 24.
    A. Polesel, G. Ramponi, V.J. Mathews, Image enhancement via adaptive unsharp masking. IEEE Trans. Image Process. 9(3), 505–510 (2000)CrossRefGoogle Scholar
  25. 25.
    Z. Rahman, D.J. Jobson, G.A. Woodell, Retinex processing for automatic image enhancement. J. Electron. Imaging 13(1), 100–110 (2004)CrossRefGoogle Scholar
  26. 26.
    D. Sheet, H. Garud, A. Suveer, M. Mahadevappa, J. Chatterjee, Brightness preserving dynamic fuzzy histogram equalization. IEEE Trans. Consum. Electron. 56(4), 2475–2480 (2010)CrossRefGoogle Scholar
  27. 27.
    C. Shen, W. Hwang, Color image enhancement using retinex with robust envelope. in Proceedings of IEEE International Conference on Image Processing, Cairo, 3141–3144 November 2009Google Scholar
  28. 28.
    Y. Shin, S. Jeong, S. Lee, Efficient naturalness restoration for nonuniform illumination images. IET Image Process. 9(8), 662–671 (2015)CrossRefGoogle Scholar
  29. 29.
    G. Thomas, D. Flores-Tapia, S. Pistorius, Histogram specification: a fast and flexible method to process digital images. IEEE Trans. Instrum. Meas. 60(5), 1565–1578 (2011)CrossRefGoogle Scholar
  30. 30.
    M. Tiwari, B. Gupta, M. Shrivastava, High speed quantile based histogram equalization for brightness preservation and contrast enhancement. IET Image Process. 9(1), 80–89 (2014)CrossRefGoogle Scholar
  31. 31.
    M. Tiwari, B. Gupta, Brightness preserving contrast enhancement of medical images using adaptive gamma correction and homomorphic filtering. in 2016 IEEE Students’ Conference on Electrical, Electronics and Computer Science (SCEECS), Bhopal, 1–4 2016Google Scholar
  32. 32.
    S. Wang, J. Zheng, H. Hu, B. Li, Naturalness preserved enhancement algorithm for non-uniform illumination images. IEEE Trans. Image Process. 22(9), 3538–3548 (2013)CrossRefGoogle Scholar
  33. 33.
    X. Zhang, B. Wandell, A spatial extension of CIELAB for digital color-image reproduction. J. Soc. Inf. Disp. 5, 61–63 (1997)CrossRefGoogle Scholar
  34. 34.
    K. Zuiderveld, Contrast limited adaptive histogram equalization, Chapter VIII, in Graphics Gems IV, ed. by P.S. Heckbert (Academic Press, Cambridge, 1994), pp. 474–485CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.SRM UniversityChennaiIndia
  2. 2.PDPM Indian Institute of Information Technology, Design and Manufacturing JabalpurJabalpurIndia

Personalised recommendations