Skip to main content
SpringerLink
Log in

Real-time haze removal in monocular images using locally adaptive processing

  • Original Research Paper
  • Published:
Journal of Real-Time Image Processing Aims and scope Submit manuscript

Abstract

This research presents the design of a real-time system to remove the effects of haze in a sequence of monocular images. The system firstly estimates the medium transmission function from an observed hazy image using locally adaptive neighborhoods and calculation of order statistics. Next, the haze-free image is retrieved using the estimated transmission function and a physics-based restoration model. The performance of the proposed system is evaluated and compared with that of similar existing techniques in terms of objective metrics. The obtained results exhibit that the proposed system yields a higher performance in comparison with tested similar methods. Because of its high computational efficiency, the proposed system is able to operate at high rate and it is suitable for real-time applications.

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
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

References

  1. Boreskov, A., Shikin, E.: Computer Graphics: From Pixels to Programmable Graphics Hardware. Chapman & Hall/CRC, London (2014)

    Google Scholar 

  2. Bui, T.M., Tran, H.N., Kim, W., Kim, S.: Segmenting dark channel prior in single image dehazing. Electron. Lett. 50(7), 516–518 (2014)

    Article  Google Scholar 

  3. Chambolle, A.: An algorithm for total variation minimization and applications. J. Math. Imaging Vis. 20(1), 89–97 (2004)

    MathSciNet  MATH  Google Scholar 

  4. Chambolle, A., Pock, T.: A first-order primal–dual algorithm for convex problems with applications to imaging. J. Math. Imaging Vis. 40(1), 120–145 (2011)

    Article  MathSciNet  Google Scholar 

  5. El-Hashash, M.M., Aly, H.A.: High-speed video haze removal algorithm for embedded systems. J. Real-Time Image Proc. (2016). doi:10.1007/s11554-016-0603-1

    Article  Google Scholar 

  6. Fattal, R.: Single image dehazing. ACM Trans. Graph. 27(3), 72:1–72:9 (2008)

    Article  Google Scholar 

  7. Gao, R., Wang, Y., Liu, M., Fan, X.: Fast algorithm for dark channel prior. Electron. Lett. 50(24), 1826–1828 (2014)

    Article  Google Scholar 

  8. He, K., Sun, J., Tang, X.: Single image haze removal using dark channel prior. IEEE Trans. Pattern Anal. Mach. Intell. 33(12), 2341–2353 (2011)

    Article  Google Scholar 

  9. He, K., Sun, J., Tang, X.: Guided image filtering. IEEE Trans. Pattern Anal. Mach. Intell. 35(6), 1397–1409 (2013)

    Article  Google Scholar 

  10. Kober, V., Mozerov, M., Alvarez-Borrego, J.: Nonlinear filters with spatially connected neighborhoods. Opt. Eng. 40(6), 971–983 (2001)

    Article  Google Scholar 

  11. Koschmieder, H.: Theorie der horizontalen sichtweite. Beitr Phys Freien Atm 12, 171–181 (1924)

    Google Scholar 

  12. Lee, S., Yun, S., Nam, J.H., Won, C.S., Jung, S.W.: A review on dark channel prior based image dehazing algorithms. EURASIP J. Image Video Process. 1, 4 (2016)

    Article  Google Scholar 

  13. Levin, A., Lischinski, D., Weiss, Y.: A closed-form solution to natural image matting. IEEE Trans. Pattern Anal. Mach. Intell. 30(2), 228–242 (2008)

    Article  Google Scholar 

  14. Liu, H., Yang, J., Wu, Z., Zhang, Q.: Fast single image dehazing based on image fusion. J. Electron. Imaging 24(1), 013020 (2015)

    Article  Google Scholar 

  15. Narasimhan, S.G., Nayar, S.K.: Vision and the atmosphere. Int. J. Comput. Vision 48(3), 233–254 (2002)

    Article  Google Scholar 

  16. Narasimhan, S.G., Nayar, S.K.: Contrast restoration of weather degraded images. IEEE Trans. Pattern Anal. Mach. Intell. 25(6), 713–724 (2003)

    Article  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  18. Schechner, Y.Y., Narasimhan, S.G., Nayar, S.K.: Polarization-based vision through haze. Appl. Opt. 42(3), 511–525 (2003)

    Article  Google Scholar 

  19. Sun, W., Guo, B.L., Li, D.J., Jia, W.: Fast single-image dehazing method for visible-light systems. Opt. Eng. 52(9), 093103–093103 (2013)

    Article  Google Scholar 

  20. Tarel, J.P., Hautire, N.: Fast visibility restoration from a single color or gray level image. In: 2009 IEEE 12th International Conference on Computer Vision, pp. 2201–2208 (2009)

  21. Wang, D., Zhu, J., Yan, F.: Dehazing for single image with sky region via self-adaptive weighted least squares model. Opt. Eng. 55(4), 043106 (2016)

    Article  Google Scholar 

  22. Wang, J.G., Tai, S.C., Lin, C.J.: Image haze removal using a hybrid of fuzzy inference system and weighted estimation. J. Electron. Imaging 24(3), 033027 (2015)

    Article  Google Scholar 

  23. Yang, J., Jiang, B., Lv, Z., Jiang, N.: A real-time image dehazing method considering dark channel and statistics features. J. Real-Time Image Proc. (2017). doi:10.1007/s11554-017-0671-x

    Article  Google Scholar 

  24. Yu, T., Riaz, I., Piao, J., Shin, H.: Real-time single image dehazing using block-to-pixel interpolation and adaptive dark channel prior. IET Image Process 9(9), 725–734 (2015)

    Article  Google Scholar 

  25. Zhu, Q., Mai, J., Shao, L.: A fast single image haze removal algorithm using color attenuation prior. IEEE Trans. Image Process. 24(11), 3522–3533 (2015)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

This research was supported by Secretaría de Investigación y Posgrado - Instituto Politécnico Nacional, project SIP20171387 and Consejo Nacional de Ciencia y Tecnología, project Catedras-CONACYT-880.

Author information

Authors and Affiliations

  1. Instituto Politécnico Nacional - CITEDI, Ave. Instituto Politécnico Nacional 1310, Nueva Tijuana, 22435, Tijuana, B.C., Mexico

    Victor H. Diaz-Ramirez & José Enrique Hernández-Beltrán

  2. CONACYT - Instituto Politécnico Nacional, CITEDI, Ave. Instituto Politécnico Nacional 1310, Nueva Tijuana, 22435, Tijuana, B.C., Mexico

    Rigoberto Juarez-Salazar

Authors
  1. Victor H. Diaz-Ramirez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. José Enrique Hernández-Beltrán
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rigoberto Juarez-Salazar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Victor H. Diaz-Ramirez.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Diaz-Ramirez, V.H., Hernández-Beltrán, J.E. & Juarez-Salazar, R. Real-time haze removal in monocular images using locally adaptive processing. J Real-Time Image Proc 16, 1959–1973 (2019). https://doi.org/10.1007/s11554-017-0698-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11554-017-0698-z

Keywords

Search

Navigation