• DocumentCode
    3385999
  • Title

    Multi-sale morphological filtering method for preserving the details of images

  • Author

    Guan Mingshan ; Ren Hong´e ; Ma Yan

  • Author_Institution
    Dept. of Comput. & Inf. Eng., Heilongjiang Inst. of Sci. & Technol., Harbin, China
  • Volume
    2
  • fYear
    2009
  • fDate
    28-29 Nov. 2009
  • Firstpage
    417
  • Lastpage
    420
  • Abstract
    A multi-sale morphological filtering method for preserving the details of images (MMFPD) was applied by adding the multi-scale top-hat transformation and bottom-hat transformation to the conventional multi-sale morphological opening and closing filtering. The two added transforms were used to extract and smooth the features which are smaller than the current scale. It was found that the smaller features have greater possibility to contain noise particles. Accordingly, the coefficients of top-hat transformation and bottom-hat transformation were modified. Simulation results on the standard gray-level images show that the method can effectively remove noise and preserve the details of images completely, and demonstrate better performance than the conventional filtering methods.
  • Keywords
    filtering theory; image processing; mathematical morphology; bottom hat transformation; contain noise particles; conventional filtering methods; gray level images; image details preservation; multisale morphological closing filtering; multisale morphological filtering method; multisale morphological opening filtering; multiscale tophat transformation; Educational institutions; Electronic mail; Filtering theory; Image processing; Information filtering; Information filters; Mean square error methods; Morphology; Nonlinear filters; Wiener filter; bottom-hat transformation; mathsmatical morphologic; multi-Scale; top-hat transformation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Industrial Applications, 2009. PACIIA 2009. Asia-Pacific Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4606-3
  • Type

    conf

  • DOI
    10.1109/PACIIA.2009.5406568
  • Filename
    5406568