• DocumentCode
    3356839
  • Title

    An illumination balance algorithm based on improved affine shadow formation model for underwater image

  • Author

    Xinnan Fan ; Peng Wu ; Jianjun Ni ; Pengfei Shi

  • Author_Institution
    Coll. of IOT Eng., Hohai Univ., Changzhou, China
  • Volume
    2
  • fYear
    2013
  • fDate
    16-18 Dec. 2013
  • Firstpage
    910
  • Lastpage
    916
  • Abstract
    The uneven illumination distribution in underwater visual inspection will lead to the difficulty of extracting texture features. The underwater image illumination balance while keeping the texture details has been one of the key issues in underwater visual inspection. Aimed at this problem, a novel illumination balance algorithm based on improved affine shadow formation model is proposed in this study. In the proposed approach, the linear spatial filter is used to obtain the light intensity distribution of an image, and the original image is divided into a series of small strips of pixels based on the light intensity distribution. Then the illumination balance of the image is carried out based on an improved affine shadow formation model. The experimental results show that the proposed approach can deal with the uneven illumination problem in underwater image, and keep the texture details effectively, which is very important for the subsequent processing and analysis for underwater images.
  • Keywords
    feature extraction; filtering theory; image texture; lighting; improved affine shadow formation model; light intensity distribution; linear spatial filter; texture feature extraction; underwater image illumination balance algorithm; underwater visual inspection; Brightness; Entropy; Lighting; Maximum likelihood detection; Nonlinear filters; Strips; Affine shadow formation model; Illumination balance processing; Linear spatial filtering; Texture preserving; Underwater image;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing (CISP), 2013 6th International Congress on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4799-2763-0
  • Type

    conf

  • DOI
    10.1109/CISP.2013.6745294
  • Filename
    6745294