• DocumentCode
    190864
  • Title

    Single image dehazing based on multiple scattering model

  • Author

    Xipan Lu ; Guoyun Lv ; Tao Lei

  • Author_Institution
    Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´an, China
  • fYear
    2014
  • fDate
    5-8 Aug. 2014
  • Firstpage
    239
  • Lastpage
    244
  • Abstract
    Most of the existing hazing algorithms are established on the assumptions of single scattering, but the multiple scattering is obvious and cannot be ignored. To obtain a better dehazing effect, we first analyze the multiple atmospheric scattering in detail and propose an image degradation model based on multiple scattering. Second, we propose a new improved method on the basis of dark channel prior. The proposed algorithm uses the semi-reverse algorithm to determine the foggy area, and then estimates the atmospheric light A from the most concentrated area; and then estimates transmission with the minimum channel of RGB; finally recover a clear image according to the multiple scattering model. Experimental results demonstrate that the proposed method achieves good restoration for contrast and color fidelity and has low computational complexity.
  • Keywords
    computational complexity; image colour analysis; image enhancement; image restoration; light scattering; atmospheric light estimation; computational complexity; dark channel prior; foggy area determination; image color fidelity; image contrast; image degradation model; image restoration; multiple atmospheric scattering; multiple scattering model; semireverse algorithm; single image dehazing; Atmospheric modeling; Channel estimation; Computational modeling; Degradation; Image color analysis; Image restoration; Scattering; dark channel prior; dehazing; multiple scattering; semi-reverse algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, Communications and Computing (ICSPCC), 2014 IEEE International Conference on
  • Conference_Location
    Guilin
  • Print_ISBN
    978-1-4799-5272-4
  • Type

    conf

  • DOI
    10.1109/ICSPCC.2014.6986190
  • Filename
    6986190