• DocumentCode
    2264396
  • Title

    An Adaptive Morphological Filter Based on Multiple Structure and Multi-Scale Elements

  • Author

    Xu, Guo-bao ; Su, Zhi-bin ; Wang, Ji ; Yin, Yi-xin ; Shen, Yu-li

  • Author_Institution
    Inf. Sch., Guangdong Ocean Univ., Zhanjiang
  • Volume
    2
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    399
  • Lastpage
    403
  • Abstract
    To filter out various kinds of noise of different intensities in gray images, a highly adaptive morphological filter based on multiple structure and multi-scale elements was proposed. This algorithm employs a morphology filter based on multiple structure and multi-scale elements to filter the images, followed by image fusion processing with the weights calculated from the image entropies, before finally obtaining the filtered images. The experimental results show that the proposed filtering algorithm, compared with the traditional filtering algorithms using the mean filter, median filter and Wiener filter, has a better adaptability. The new algorithm can effectively filter many kinds of noise such as the salt and pepper noise, Gaussian noise and speckle noise, while preserving more image details.
  • Keywords
    Gaussian noise; Wiener filters; adaptive filters; image fusion; median filters; speckle; Gaussian noise; Wiener filter; adaptive morphological filter; filtering algorithm; gray images; image entropies; image filter; image fusion processing; mean filter; median filter; multi-scale elements; multiple structure; salt-and-pepper noise; speckle noise; Adaptive filters; Filtering algorithms; Gaussian noise; Image analysis; Image processing; Information technology; Intelligent structures; Morphology; Shape; Wiener filter; Entropy; Image filtering; Mathematical morphology; Multi-scale elements; Multiple structure elements;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3497-8
  • Type

    conf

  • DOI
    10.1109/IITA.2008.359
  • Filename
    4739794