Multimedia Tools and Applications

, Volume 77, Issue 3, pp 3125–3141 | Cite as

Nighttime image Dehazing with modified models of color transfer and guided image filter

  • Bo Jiang
  • Hongqi Meng
  • Xiaolei Ma
  • Lin Wang
  • Yan Zhou
  • Pengfei Xu
  • Siyu Jiang
  • Xianjia Meng


Taking into account of the illumination characteristics of nighttime imaging, a new method for nighttime image dehazing is proposed in this paper. In the first place, based on the color transfer theory, the illumination level of nighttime hazy image can be artificially enhanced through flexibly selecting the reference image. In contrast to the classical model of color transfer with the strategy of overall to overall transfer, the modified model focuses on the different characteristics of various regions in the original image, and it works well even though the nighttime image is interfered by various artificial light sources. In the second place, the enhancement dehazing method based on the theory of guided image filtering is adopted since the key parameters of dehazing method using the atmospheric degradation model are difficult to obtain in the conditions of nighttime imaging. In addition, the key model parameters of guided image filter are selected according to the boundary information of original image rather than the original image itself, which makes it more advantageous for dehazing image taken on the hazy night. The experimental results show that the proposed method has better performance than the classical daytime dehazing methods. Additionally, our method exhibits superior effect compared to the well-known nighttime dehazing method in the aspects of suppressing color distortion and background illumination controlling. The evaluations of the experimental results are established on both the subjective and objective aspects, so the conclusion in this paper is more convincing.


Nighttime image Image dehazing Color transfer Guided image filtering 



This work was supported by National Natural Science Foundation of China (No. 41601353, 61503300 and 61502387), and Foundation of Key Laboratory of Space Active Opto-Electronics Technology of Chinese Academy of Sciences (No. AOE-2016-A02), and Scientific Research Program Funded by Shaanxi Provincial Education Department (No. 16JK1765), and Foundation of State Key Laboratory of Transient Optics and Photonics, Chinese Academy of Sciences (No. SKLST201614), and Natural Science Basic Research Plan in Shaanxi Province of China (No. 2017JQ4003).


  1. 1.
    Bui TM, Tran HN, Kim W, Kim S (2014) Segmenting dark channel prior in single image dehazing. Electron Lett 50(7):516–518CrossRefGoogle Scholar
  2. 2.
    Chang X, Yu YL, Yang Y, Xing EP (2016) Semantic Pooling for Complex Event Analysis in Untrimmed Videos. IEEE Trans Pattern Anal Mach Intell. doi: 10.1109/TPAMI.2016.2608901
  3. 3.
    Chen B-H, Huang S-C, Ye JH (2015) Hazy image restoration by bi-histogram modification. ACM Trans Intell Syst Technol 6(4):1–17CrossRefGoogle Scholar
  4. 4.
    Cheng FC, Lin CH, Lin JL (2012) Constant time O(1) image fog removal using lowest level channel. Electron Lett 48(22):1404–1406CrossRefGoogle Scholar
  5. 5.
    Fattal R (2008) Single image dehazing. ACM Trans Graph 27(3):1–9CrossRefGoogle Scholar
  6. 6.
    He K, Sun J, Tang X (2010) Single image haze removal using dark channel prior. IEEE Trans Pattern Anal Mach Intell 33(12):2341–2353Google Scholar
  7. 7.
    He K, Sun J, Tang X (2013) Guided image filtering. IEEE Trans Pattern Anal Mach Intell 35(6):1397–1409CrossRefGoogle Scholar
  8. 8.
    Huang S-C, Ye J-H, Chen B-H (2015) An advanced single image visibility restoration algorithm for real-world hazy scenes. IEEE Trans Ind Electron 62(5):2962–2972CrossRefGoogle Scholar
  9. 9.
    Jiang B, Zhang W, Meng H, Ru Y, Zhang Y, Ma X (2015) Single image haze removal on complex imaging background. IEEE International Conference on Software Engineering and Service Sciences 280–283Google Scholar
  10. 10.
    Jiang B, Zhang W, Zhao J, Ru Y, Liu M, Ma X, Chen X, Meng H (2016) Gray-scale image dehazing guided by scene depth information. Math Probl Eng 2016:1–10Google Scholar
  11. 11.
    Kou F, Chen W, Wen C, Li Z (2015) Gradient domain guided image filtering. IEEE Trans Image Process 24(11):4528–4539MathSciNetCrossRefGoogle Scholar
  12. 12.
    Li Y, Tan RT, Brown MS (2015) Nighttime haze removal with glow and multiple light colors. IEEE Int Conf Comput Vis 226-234Google Scholar
  13. 13.
    Li Z, Zheng J, Zhu Z, Yao W, Wu S (2015) Weighted guided image filtering. IEEE Trans Image Process 24(1):120–129MathSciNetCrossRefGoogle Scholar
  14. 14.
    Lu H, Li Y, Nakashima S, Serikawa S (2016) Single image dehazing through improved atmospheric light estimation. Multimed Tool Appl 75(24):17081–17096CrossRefGoogle Scholar
  15. 15.
    Luo M, Chang X, Nie L, Yang Y, Hauptmann A, Zheng Q (2017) An Adaptive Semisupervised Feature Analysis for Video Semantic Recognition. IEEE Trans Cybern. doi: 10.1109/TCYB.2017.2647904
  16. 16.
    Mittal A, Moorthy AK, Bovik AC (2012) No-reference image quality assessment in the spatial domain. IEEE Trans Image Process 21(12):4695–4708MathSciNetCrossRefMATHGoogle Scholar
  17. 17.
    Pei SC, Lee TY (2012) Nighttime haze removal using color transfer pre-processing and dark channel prior. IEEE Int Conf Image Proc:957–960Google Scholar
  18. 18.
    Reinhard E, Ashikhmin M, Gooch B, Shirley P (2001) Color transfer between images. IEEE Comput Graph Appl 21(5):34–41CrossRefGoogle Scholar
  19. 19.
    Shi Z, Xu B, Zheng X, Zhao M (2016) An integrated method for ancient Chinese tablet images de-noising based on assemble of multiple image smoothing filters. Multimed Tool Appl 75(19):12245–12261CrossRefGoogle Scholar
  20. 20.
    Tarel JP, Hautière N (2009) Fast visibility restoration from a single color or gray level image. IEEE Int Conf Comput Vis 30(2):2201–2208Google Scholar
  21. 21.
    Zheng X, Miao Q, Shi Z, Fan Y, Shui W (2016) A new artistic information extraction method with multi channels and guided filters for calligraphy works. Multimed Tool Appl 75(14):8719–8744CrossRefGoogle Scholar
  22. 22.
    Zhu Q, Mai J, Shao L (2015) A Fast Single Image Haze Removal Algorithm Using Color Attenuation Prior. IEEE Trans Image Process 24(11):3522–3533MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Bo Jiang
    • 1
  • Hongqi Meng
    • 1
  • Xiaolei Ma
    • 2
  • Lin Wang
    • 1
  • Yan Zhou
    • 1
  • Pengfei Xu
    • 1
  • Siyu Jiang
    • 3
  • Xianjia Meng
    • 1
  1. 1.School of Information and TechnologyNorthwest UniversityXi’anChina
  2. 2.Department of PhysicsEmory UniversityAtlantaUSA
  3. 3.School of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’anChina

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