• DocumentCode
    2338735
  • Title

    A new method for foggy image enhancment

  • Author

    Feng, Yan ; He, Mingyi ; Liu, Weihua

  • Author_Institution
    Shaanxi Key Lab. of Inf. Acquisition & Process., Northwestern Polytech. Univ., Xi´´an
  • fYear
    2009
  • fDate
    25-27 May 2009
  • Firstpage
    2416
  • Lastpage
    2419
  • Abstract
    As a common natural phenomenon, fog makes photographed images blurred, thus bringing great difficulty for monitoring of outdoors image, target identification and tracking and so on. In this paper, the authors propose a new method for foggy image enhancement that integrates multilevel wavelet decomposition, the auto-adapted LUM filter, soft threshold and so on. Firstly, carry on the multilevel wavelet decomposition to the image, and then obtain the low-frequency component and high-frequency components of image, use the auto-adapted LUM filter to low-frequency component, while utilize soft threshold based on Bayes estimation to process high-frequency components, and eventually carry on wavelet restructuring to the processed components. Through simulation, this method is proved to be superior to traditional methods in foggy image enchantment.
  • Keywords
    Bayes methods; filtering theory; fog; image enhancement; image reconstruction; image segmentation; target tracking; wavelet transforms; Bayes estimation; autoadapted LUM filter; foggy image enhancement; image blurring; multilevel wavelet decomposition; natural phenomenon; outdoor image monitoring; soft threshold; target identification; tracking method; wavelet restructuring; Atmospheric modeling; Filters; Frequency domain analysis; Helium; Image enhancement; Smoothing methods; Space technology; Target tracking; Wavelet analysis; Wavelet domain; autoadapted LUM filter; image enhancing; threshold process; wavelet decompose;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4244-2799-4
  • Electronic_ISBN
    978-1-4244-2800-7
  • Type

    conf

  • DOI
    10.1109/ICIEA.2009.5138634
  • Filename
    5138634