• DocumentCode
    3265453
  • Title

    Visibility Enhancement for Roads with Foggy or Hazy Scenes

  • Author

    Tan, Robby T. ; Pettersson, Niklas ; Petersson, Lars

  • Author_Institution
    Australian Nat. Univ., Canberra
  • fYear
    2007
  • fDate
    13-15 June 2007
  • Firstpage
    19
  • Lastpage
    24
  • Abstract
    Bad weather, particularly fog and haze, commonly obstruct drivers from observing road conditions. This could frequently lead to a considerable number of road accidents. To avoid the problem, automatic methods have been proposed to enhance visibility in bad weather. Methods that work on visible wavelengths, based on the type of their input, can be categorized into two approaches: those using polarizing filters, and those using images taken from different fog densities. Both of the approaches require that the images are multiple and taken from exactly the same point of view. While they can produce reasonably good results, their requirement makes them impractical, particularly in real time applications, such as vehicle systems. Considering their drawbacks, our goal is to develop a method that requires solely a single image taken from ordinary digital cameras, without any additional hardware. The method principally uses color and intensity information. It enhances the visibility after estimating the color of skylight and the values of airtight. The experimental results on real images show the effectiveness of the approach.
  • Keywords
    estimation theory; filtering theory; image colour analysis; image enhancement; image sensors; road accidents; road traffic; road vehicles; weather forecasting; airtight value estimation; bad weather visibility; digital cameras; fog densities; foggy scenes; hazy scenes; polarizing filters; road accidents; road visibility enhancement; skylight color estimation; vehicle systems; Digital cameras; Filters; Intelligent vehicles; Laser radar; Layout; Optical attenuators; Optical reflection; Polarization; Real time systems; Roads;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium, 2007 IEEE
  • Conference_Location
    Istanbul
  • ISSN
    1931-0587
  • Print_ISBN
    1-4244-1067-3
  • Electronic_ISBN
    1931-0587
  • Type

    conf

  • DOI
    10.1109/IVS.2007.4290085
  • Filename
    4290085