• DocumentCode
    3263442
  • Title

    The Enhancement for Foggy Traffic Image Based on EM Algorithm

  • Author

    Xianqiao, Chen ; Qing, Wu ; Xinping, Yan ; Xiumin, Chu

  • Author_Institution
    Sch. of Comp., Wuhan Univ. of Tech., Wuhan, China
  • Volume
    2
  • fYear
    2009
  • fDate
    6-7 June 2009
  • Firstpage
    261
  • Lastpage
    264
  • Abstract
    In bad weather, such as foggy, the vision become poor, and this often induce many problems for traffic safety. So it is a hot research subject how to improve the vision ability for bad weather in traffic, and there are many achievements have been made. Among these the single scale Retinex algorithm is a common used method, which was proposed by Land. According this theory, any obtained image can be divided into two images: illumination image and object reflected image. If the illumination can be estimated accurately, the high quality enhanced image (reflected image) will be obtained easily. In this paper, one efficient method (EFTI-EM) for illumination was proposed, which is used to estimate the illumination by using sky area in a foggy traffic image and to get sky area is based on EM algorithm. By setting a considerable number of tests, satisfactory results have been achieved.
  • Keywords
    expectation-maximisation algorithm; image enhancement; road safety; road traffic; traffic engineering computing; EM algorithm; bad weather; foggy traffic image enahancement; illumination image; object reflected image; single scale Retinex algorithm; sky area; traffic safety; Computational intelligence; Computer vision; Humans; Laser radar; Lighting; Machine vision; Reflectivity; Safety; Testing; Traffic control; EM algorithm; Foggy image; Illuminations; Image enhancement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3645-3
  • Type

    conf

  • DOI
    10.1109/CINC.2009.122
  • Filename
    5230973