Skip to main content
Top

2015 | OriginalPaper | Chapter

Haze Removal: An Approach Based on Saturation Component

Authors : Khitish Kumar Gadnayak, Pankajini Panda, Niranjan Panda

Published in: Intelligent Computing, Communication and Devices

Publisher: Springer India

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Outdoor images those are taken under bad weather conditions are basically degraded by the various atmospheric particles such as smoke, fog, and haze. Due to the atmospheric absorption and scattering phenomena while capturing the images, the irradiance received by the camera from the scene point is attenuated along the line of sight. The incoming light flux is attenuated with the light from all other directions called the airlight. Due to this reason, there is a resultant decay in the color and the contrast of the captured image. Haze removal from an input image or dehazing of an image is highly required so as to increase the visibility of the input image. Removing the haze layer from the input hazy image can significantly increase the visibility of the scene. The haze-free image is basically visually pleasing in nature. The paper focuses on the haze removal process by considering the HSI color model of an image instead of RGB color space. In the HSI color model, the saturation component describes the contrast of an image. From the saturation component, it is possible to estimate the transmission coefficient or the alpha map, and from this, a haze-free image can be recovered which has the better visibility than that of the captured hazy image.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Schechner, Y.Y., Narasimhan, S.G., Nayar, S.K.: Instant dehazing of images using polarization. In: Proceedings IEEE Conference Computer Vision and Pattern Recognition, vol. 1, pp. 325–332 (2001) Schechner, Y.Y., Narasimhan, S.G., Nayar, S.K.: Instant dehazing of images using polarization. In: Proceedings IEEE Conference Computer Vision and Pattern Recognition, vol. 1, pp. 325–332 (2001)
2.
go back to reference Narasimhan, S., Nayar, S.: Vision in bad weather. In: Proceedings IEEE International Conference on Computer Vision, pp. 820–827 (1999) Narasimhan, S., Nayar, S.: Vision in bad weather. In: Proceedings IEEE International Conference on Computer Vision, pp. 820–827 (1999)
3.
go back to reference Narasimhan, S.G., Nayar, S.K.: Chromatic framework for vision in bad weather. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 598–605 (2000) Narasimhan, S.G., Nayar, S.K.: Chromatic framework for vision in bad weather. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 598–605 (2000)
4.
go back to reference Narasimhan, S.G., Nayar, S.K.: Contrast restoration of weather degraded images. IEEE Trans. Pattern Anal. Mach. Intell. 25(6), 713–724 (2003)CrossRef Narasimhan, S.G., Nayar, S.K.: Contrast restoration of weather degraded images. IEEE Trans. Pattern Anal. Mach. Intell. 25(6), 713–724 (2003)CrossRef
5.
go back to reference Tan, R.: Visibility in bad weather from a single image. In: Proceedings IEEE Conference Computer Vision and Pattern Recognition (2008) Tan, R.: Visibility in bad weather from a single image. In: Proceedings IEEE Conference Computer Vision and Pattern Recognition (2008)
6.
go back to reference Fattal, R.: Single image dehazing. ACM Trans. Graph. SIGGRAPH 27(3), 72 (2008) Fattal, R.: Single image dehazing. ACM Trans. Graph. SIGGRAPH 27(3), 72 (2008)
7.
go back to reference He, K., Sun, J., Tang, X.: Single image haze removal using dark channel prior. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1957–1963 (2009) He, K., Sun, J., Tang, X.: Single image haze removal using dark channel prior. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1957–1963 (2009)
8.
go back to reference Ancuti, C.O., Ancuti, C., Bekaert, P.: Effective single image dehazing by fusion. In: 17th IEEE International Conference on IEEE Image Processing (ICIP) (2010) Ancuti, C.O., Ancuti, C., Bekaert, P.: Effective single image dehazing by fusion. In: 17th IEEE International Conference on IEEE Image Processing (ICIP) (2010)
9.
go back to reference Chu, C.-T., Lee, M.-S.: A content-adaptive method for single image dehazing. Advances in Multimedia Information Processing, pp. 350–361 (2011) Chu, C.-T., Lee, M.-S.: A content-adaptive method for single image dehazing. Advances in Multimedia Information Processing, pp. 350–361 (2011)
10.
go back to reference Levin, A., Lischinski, D., Weiss, Y.: A closed form solution to natural image matting. In: Proceedings IEEE Conference Computer Vision and Pattern Recognition, vol. 1, pp. 61–68 (2006) Levin, A., Lischinski, D., Weiss, Y.: A closed form solution to natural image matting. In: Proceedings IEEE Conference Computer Vision and Pattern Recognition, vol. 1, pp. 61–68 (2006)
11.
go back to reference Xie, B., Guo, F., Cai, Z.: Improved single image dehazing using dark channel prior and multi-scale Retinex. Intelligent System Design and Engineering Application (2010) Xie, B., Guo, F., Cai, Z.: Improved single image dehazing using dark channel prior and multi-scale Retinex. Intelligent System Design and Engineering Application (2010)
12.
go back to reference Gadnayak, K.K., Panda, P., Panda, N.: A survey on image dehazing. Int. J. Eng. Res. Technol. 462–466 (2013) Gadnayak, K.K., Panda, P., Panda, N.: A survey on image dehazing. Int. J. Eng. Res. Technol. 462–466 (2013)
Metadata
Title
Haze Removal: An Approach Based on Saturation Component
Authors
Khitish Kumar Gadnayak
Pankajini Panda
Niranjan Panda
Copyright Year
2015
Publisher
Springer India
DOI
https://doi.org/10.1007/978-81-322-2009-1_33

Premium Partner