• DocumentCode
    3094110
  • Title

    A Classification Algorithm to Distinguish Image as Haze or Non-haze

  • Author

    Yu, Xiaoliang ; Xiao, Chuangbai ; Deng, Mike ; Peng, Li

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Beijing Univ. of Technol., Beijing, China
  • fYear
    2011
  • fDate
    12-15 Aug. 2011
  • Firstpage
    286
  • Lastpage
    289
  • Abstract
    The technology of image dehazing can only work for haze images, but in batch and real-time processing, only relying on human visual system judge whether the image is haze or non-haze image, is unrealistic, so how to determine whether there are haze or non-haze images is needed to be solved. In this paper, we proposed a method to judge whether a given image is haze. According to the difference between the haze and non-haze images, we extract three eigen values, including image visibility, intensity of dark channel and image contrast, then combine with support vector machine to make judgment of image state which is haze or non-haze, obtaining high recognition rate. Experimental results show that our method is feasible and effective. Our method for bath and real-time processing provide the basis for judging image state, promoting the wide application of image dehazing.
  • Keywords
    eigenvalues and eigenfunctions; image classification; support vector machines; SVM; batch processing; dark channel intensity; eigenvalues; haze images; human visual system; image classification algorithm; image contrast; image dehazing; image state; image visibility; nonhaze images; real-time processing; support vector machine; Eigenvalues and eigenfunctions; Feature extraction; Histograms; Humans; Image color analysis; Image edge detection; Support vector machines; distingussish image state; haze image; non-haze image; suppotr vector machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Graphics (ICIG), 2011 Sixth International Conference on
  • Conference_Location
    Hefei, Anhui
  • Print_ISBN
    978-1-4577-1560-0
  • Electronic_ISBN
    978-0-7695-4541-7
  • Type

    conf

  • DOI
    10.1109/ICIG.2011.22
  • Filename
    6005597