• DocumentCode
    2139469
  • Title

    New Morphological Filtering Algorithm for Image Noise Reduction

  • Author

    Huang, Cheng ; Zhu, Youlian

  • Author_Institution
    Coll. of Electron. Inf. Eng., Jiangsu Teachers Univ. of Technol., Changzhou, China
  • fYear
    2009
  • fDate
    17-19 Oct. 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Conventional morphological filter is disabling to effectively preserve image details while removing noises from an image. The proposed algorithm of the self adaptive median morphological filter is implemented as follows. First, the extreme value operation is displaced by the median operation in erosion and dilation. Then, the structuring element unit (SEU) is built based on the zero square matrix. Finally, the peak signal to noise ratio (PSNR) is used as the estimation function to select the size of the structuring element. Simulation results show that the proposed filter can effectively resolve the problem between detail-preserving and noise-removing, and its performance is obviously superior to others especially in the low signal to noise ratio situation. When the noise density is 75%, its PSNR is higher 11-14 dB than the conventional morphological filter and 10-12 dB than the median filter.
  • Keywords
    image denoising; median filters; estimation function; extreme value operation; image noise reduction; median filter; median operation; morphological filtering algorithm; peak signal to noise ratio; self adaptive median morphological filter; structuring element unit; zero square matrix; Filtering algorithms; Filters; Morphological operations; Morphology; Noise reduction; PSNR; Performance analysis; Signal processing algorithms; Signal to noise ratio; Visual effects;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-1-4244-4129-7
  • Electronic_ISBN
    978-1-4244-4131-0
  • Type

    conf

  • DOI
    10.1109/CISP.2009.5303495
  • Filename
    5303495