• DocumentCode
    3447869
  • Title

    Oil film denoising method based on jump regression analysis

  • Author

    Hua-jun Song ; Peng Ren ; Wei-fang Liu

  • Author_Institution
    Coll. of Inf. & Control Eng., China Univ. of Pet.(East China), Dongying, China
  • fYear
    2012
  • fDate
    16-18 Oct. 2012
  • Firstpage
    326
  • Lastpage
    329
  • Abstract
    The key process of Ship-borne/shore-based radar image oil film recognition method is image denoising. In order to overcome the disadvantage of image edge blur produced by traditional denoising method, the Jump Regression Analysis(JRA) is used to remove radar image noise. Moreover, an improved JRA algorithm is also proposed which improves the denoising effect and reduces the run time of the JAR. It is proved by experiment that the proposed method not only can effectively remove the noise of radar image, but also to maintain the oil film edge information.
  • Keywords
    edge detection; image denoising; image recognition; image restoration; oil pollution; radar imaging; regression analysis; ships; JAR run time reduction; image edge blurring; jump regression analysis; oil film denoising effect improvement; oil film edge information; radar image noise removal; ship-borne/shore-based radar image oil film recognition method; Films; Image edge detection; Noise; Noise reduction; Radar imaging; Synthetic aperture radar; JRA; Radar imaging; image denoising; oil recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing (CISP), 2012 5th International Congress on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4673-0965-3
  • Type

    conf

  • DOI
    10.1109/CISP.2012.6469934
  • Filename
    6469934