Skip to main content
SpringerLink
Log in

Bézier curve-based saturation-aided optimal brightness adjustment for dark image clearness enhancement with image fusion

  • Original Paper
  • Published:
Signal, Image and Video Processing Aims and scope Submit manuscript

Abstract

To solve such problems as insufficient illumination improvement and unnatural visual effects in the existing dark image enhancement approaches, we propose a Bézier curve-based and saturation-aided dark image enhancement method with image fusion. Firstly, a saturation-aided preliminary brightness map estimation approach is put forward. Both saturation and brightness information are utilized to compensate the illumination information, which makes for more colorful results. Then, an evaluation function based on the preliminary brightness map is devised to get an optimal Bézier curve for the illumination adjustment purpose. Bézier curve is more flexible than traditional curves, so it can be used to improve the illumination of dark images in various types. Secondly, we handle the potential overexposure and detail loss in the optimized brightness map by fusing it with the original as well as the CLAHE-processed brightness maps. And, a mask fusion strategy is designed to avoid over-enhancement for the area that is supposed to be smooth. Finally, the enhanced brightness map is combined with the original hue and saturation channels to get our enhanced results, which present richer details and look more vivid. Our method is quantitatively evaluated with NIQE and gets a high score 3.70 on a 101 dark image dataset, which is the best among the state-of-the-art approaches compared.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Bhatnagar, G., Liu, Z.: A novel image fusion framework for night-vision navigation and surveillance. Signal Image Video Process. 9(1), 165–175 (2015)

    Article  Google Scholar 

  2. Cheng, H.D., Shi, X.J.: A simple and effective histogram equalization approach to image enhancement. Digtal Signal Process. 14(2), 158–170 (2004)

    Article  Google Scholar 

  3. Zuiderveld, K.: Contrast limited adaptive histogram equalization. In: Graphics Gems IV, pp. 474–485 (1994)

  4. Land, E.H., McCann, J.J.: Lightness and retinex theory. J. Opt. Soc. Am. 61(1), 1–11 (1971)

    Article  Google Scholar 

  5. Jobson, D.J., Rahman, Z., Woodell, G.A.: Properties and performance of a center/surround retinex. IEEE Trans. Image Process. 6(3), 451–462 (1997)

    Article  Google Scholar 

  6. Jiang, X., Yao, H., Liu, D.: Nighttime image enhancement based on image decomposition. Signal Image Video Process. 13(1), 189–197 (2019)

    Article  Google Scholar 

  7. Fu, X., Zeng, D., Huang, Y., Zhang, X., Ding, X.: A weighted variational model for simultaneous reflectance and illumination estimation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2782–2790 (2016)

  8. Cai, B., Xu, X., Guo, K., Jia, K., Hu, B., Tao, D.: A joint intrinsic-extrinsic prior model for retinex. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 4000–4009 (2017)

  9. Wang, S., Zheng, J., Hu, H., Li, B.: Naturalness preserved enhancement algorithm for non-uniform illumination images. IEEE Trans. Image Process. 22(9), 3538–3548 (2013)

    Article  Google Scholar 

  10. Guo, X., Li, Y., Ling, H.: Lime: Low-light image enhancement via illumination map estimation. IEEE Trans. Image Process. 26(2), 982–993 (2017)

    Article  MathSciNet  Google Scholar 

  11. Fu, X., Zeng, D., Huang, Y., Liao, Y., Ding, X., Paisley, J.: A fusion-based enhancing method for weakly illuminated images. Signal Process. 129, 82–96 (2016)

    Article  Google Scholar 

  12. Shan, Q., Jia, J., Brown, M.S.: Globally optimized linear windowed tone mapping. IEEE Trans. Vis. Comput. Gr. 16(4), 663–675 (2010)

    Article  Google Scholar 

  13. Chen, C., Chen, Q., Xu, J., Koltun, V.: Learning to see in the dark. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3291–3300 (2018)

  14. Keshav, V., GVSL, T.P.: Decoupling semantic context and color correlation with multi-class cross branch regularization. In: Proceedings of the IEEE International Conference on Multimedia and Expo, IEEE, pp. 1492–1497 (2019)

  15. Burt, P., Adelson, E.: The laplacian pyramid as a compact image code. IEEE Trans. Commun. 31(4), 532–540 (1983)

    Article  Google Scholar 

  16. Park, S.J., Krishna, K.: Method of enhancing contrast using bezier curve (2013). US Patent 8,577,141

  17. Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9(1), 62–66 (1979)

    Article  Google Scholar 

  18. Yan, Y.: Genetic algorithm toolbox for matlab, v1.2. http://uos-codem.github.io/GA-Toolbox. Accessed: 2019

  19. Mittal, A., Soundararajan, R., Bovik, A.C.: Making a completely blind image quality analyzer. IEEE Signal Process. Lett. 20(3), 209–212 (2013)

    Article  Google Scholar 

Download references

Acknowledgements

We’d like to thank all the anonymous reviewers for their helpful comments. This work is funded by the National Natural Science Foundation of China under Grant No. 61379075 and the Zhejiang Provincial Natural Science Foundation of China under Grant No. LY14F020004.

Author information

Authors and Affiliations

  1. School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, China

    Zhichun Lu, Chunxiao Liu & Xiaojie Zhong

Authors
  1. Zhichun Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chunxiao Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiaojie Zhong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chunxiao Liu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lu, Z., Liu, C. & Zhong, X. Bézier curve-based saturation-aided optimal brightness adjustment for dark image clearness enhancement with image fusion. SIViP 14, 1625–1633 (2020). https://doi.org/10.1007/s11760-020-01697-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11760-020-01697-1

Keywords

Search

Navigation