IDEAS home Printed from https://ideas.repec.org/a/bpj/jossai/v8y2020i5p476-486n6.html
   My bibliography  Save this article

Image Defogging Algorithm Based on Sky Region Segmentation and Dark Channel Prior

Author

Listed:
  • Jiang Zuyun
  • Wang Xiaochun

    (College of Sciences, Beijing Forestry University, Beijing100083, China)

  • Sun Xiangdong

    (College of Sciences, North China University of Technology, Beijing100144, China)

Abstract

Based on image segmentation and the dark channel prior, this paper proposes a fog removal algorithm in the HSI color space. Usually, the dark channel prior based defogging methods easily produce color distortion and halo effect when applied on images with a large sky area, because the sky region does not meet the prior assumption. For this reason, our method presents a new threshold sky region segmentation algorithm using the initial transmission map of the intensity component I. Based on the segmentation result, the initial transmission map is modified in turn, and finally refined by the guided filter. The saturation components S is reconstructed using the low frequencies of the V-transform to reduce noise, and stretched by multiplying a constant related to the initial transmission map. Experimental results show that the proposed algorithm has low time complexity and compelling fog removal result in both visual effect and quantitative measurement.

Suggested Citation

  • Jiang Zuyun & Wang Xiaochun & Sun Xiangdong, 2020. "Image Defogging Algorithm Based on Sky Region Segmentation and Dark Channel Prior," Journal of Systems Science and Information, De Gruyter, vol. 8(5), pages 476-486, October.
  • Handle: RePEc:bpj:jossai:v:8:y:2020:i:5:p:476-486:n:6
    DOI: 10.21078/JSSI-2020-476-11
    as

    Download full text from publisher

    File URL: https://doi.org/10.21078/JSSI-2020-476-11
    Download Restriction: no

    File URL: https://libkey.io/10.21078/JSSI-2020-476-11?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:jossai:v:8:y:2020:i:5:p:476-486:n:6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.