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Dehazing and Defogging

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Computer Vision

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Synonyms

Visibility enhancement in bad weather

Related Concepts

Definition

Image dehazing (or dehazing, for short) is a process to visually improve the visibility of images or videos degraded by haze or dust particles. Defogging is a similar process yet focusing on fog, which, unlike haze, is caused by water particles. Both dehazing and defogging are part of algorithms to enhance visibility in bad weather caused by light being scattered and absorbed by atmospheric particles. Since haze/fog can be present in day or night, dehazing/defogging algorithms have been developed to handle these two conditions.

Background

Poor visibility in outdoor scenes generates significant problems for many applications of computer vision. Most automatic systems for surveillance, intelligent vehicles, object recognition, etc. assume the input images have clear visibility....

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References

  1. Encyclopedia-Britannica. http://www.britannica.com

  2. Kumar B, Marshall D, DeRemer D (2005) An illustrated dictionary of aviation. McGraw-Hill Companies. India

    Google Scholar 

  3. Chandrasekhar S (1960) Radiative transfer. Dover, New York

    MATH  Google Scholar 

  4. Nayar SK, Narasimhan SG (1999) Vision in bad weather. ICCV (2):820–827

    Google Scholar 

  5. Narasimhan SG, Nayar SK (2003) Contrast restoration of weather degraded images. IEEE PAMI 25(6):713–724

    Article  Google Scholar 

  6. Beer A (1852) Bestimmung der absorption des rothen lichts in farbigen flussigkeiten. Ann Phys Chem 86(2):78–90

    Article  Google Scholar 

  7. Koschmieder H (1924) Theorie der horizontalen sichtweite. eitr. Phys Freien Atm 12

    Google Scholar 

  8. McCartney E (1975) Optics of the atmosphere: scattering by molecules and particles. John Wiley and Son

    Google Scholar 

  9. Narasimhan S, Nayar S (2003) Interactive deweathering of an image using physical models. In: IEEE Workshop on Color and Photometric Method in Computer Vision

    Google Scholar 

  10. Schechner YY, Narasimhan SG, Nayar SK (2001) Instant dehazing of images using polarization. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2001), vol 1. IEEE I–I

    Google Scholar 

  11. Shwartz S, Namer E, Schechner Y (2006) Blind haze separation. In: CVPR

    Book  Google Scholar 

  12. Treibitz T, Schechner YY (2009) Polarization: Beneficial for visibility enhancement? In: CVPR, pp 525–532

    Google Scholar 

  13. Tan K, Oakley J (2001) Physics-based approach to color image enhancement in poor visibility conditions. JOSA A. 18(10):2460–2467

    Article  Google Scholar 

  14. Hautiere N, Tarel J, Aubert D (2007) Toward fog-free in-vehicle vision systems through contrast restoration. In: CVPR

    Book  Google Scholar 

  15. Kopf J, Neubert B, Chen B, Cohen M, Cohen-Or D, Deussen O, Uyttendaele M, Lischinski D (2008) Deep photo: model-based photograph enhancement and viewing. ACM Trans Graph 27:116:1–116:10

    Google Scholar 

  16. Tan RT (2008) Visibility in bad weather from a single image. In: Proceedings of IEEE CVPR

    Book  Google Scholar 

  17. Fattal R (2008) Single image dehazing. ACM Trans Graph (TOG) 27(3):1–9

    Article  Google Scholar 

  18. He K, Sun J, Tang X (2010) Single image haze removal using dark channel prior. IEEE Trans Pattern Anal Mach Intell 33(12):2341–2353

    Google Scholar 

  19. Tarel JP, Hautière N (2009) Fast visibility restoration from a single color or gray level image. In: Proceedings of IEEE International Conference on Computer Vision (ICCV’09), Kyoto, Japan, pp 2201–2208

    Google Scholar 

  20. Berman D, Avidan S, et al. (2016) Non-local image dehazing. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 1674–1682

    Google Scholar 

  21. Li Y, You S, Brown MS, Tan RT (2017) Haze visibility enhancement: a survey and quantitative benchmarking. Comput Vis Image Underst 165:1–16

    Article  Google Scholar 

  22. Cai B, Xu X, Jia K, Qing C, Tao D (2016) Dehazenet: an end-to-end system for single image haze removal. IEEE Trans Image Process 25(11):5187–5198

    Article  MathSciNet  MATH  Google Scholar 

  23. Li B, Ren W, Fu D, Tao D, Feng D, Zeng W, Wang Z (2018) Benchmarking single-image dehazing and beyond. IEEE Trans Image Process 28(1):492–505

    Article  MathSciNet  MATH  Google Scholar 

  24. Li Y, Tan RT, Brown MS (2015) Nighttime haze removal with glow and multiple light colors. In: Proceedings of the IEEE International Conference on Computer Vision, pp 226–234

    Google Scholar 

  25. Zhang J, Cao Y, Fang S, Kang Y, Wen Chen C (2017) Fast haze removal for nighttime image using maximum reflectance prior. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 7418–7426

    Google Scholar 

  26. Wending Y, Tan RT, D. Dai (2020) Nighttime defogging using high-low frequency decomposition and grayscale-color networks. In: Proceedings of European Conference on Computer Vision

    Google Scholar 

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Author information

Authors and Affiliations

  1. Yale-NUS College, National University of Singapore, Singapore, Singapore

    Robby T. Tan

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  1. Robby T. Tan
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Correspondence to Robby T. Tan .

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Tan, R.T. (2020). Dehazing and Defogging. In: Computer Vision. Springer, Cham. https://doi.org/10.1007/978-3-030-03243-2_553-1

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  • DOI: https://doi.org/10.1007/978-3-030-03243-2_553-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03243-2

  • Online ISBN: 978-3-030-03243-2

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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