• DocumentCode
    1887203
  • Title

    Technique for mixed noise reduction based on support vector machine [image denoising]

  • Author

    Fujiki, Amanda ; Matsushita, J. ; Imai, Tetsuro ; Muneyasu, Mitsuji

  • Author_Institution
    Kansai Univ., Osaka, Japan
  • fYear
    2005
  • fDate
    18-20 May 2005
  • Firstpage
    25
  • Abstract
    Summary form only given. In this paper, we propose a new noise reduction method for images based on support vector machines (SVM). This method classifies pixels by their local features and processes them by a suitable method according to their features. In the proposed method, white Gaussian noise reduction with edge preservation is especially considered. The mixed noise reduction technique, based on a combination of the proposed method and an impulse noise reduction filter by using the SVM, is also described. Simulation results show the effectiveness of the proposed method for the reduction of white Gaussian noise and mixed noise with edge preservation.
  • Keywords
    Gaussian noise; image denoising; impulse noise; support vector machines; SVM; edge preservation; image denoising; impulse noise reduction filter; mixed noise reduction; pixel local feature classification; support vector machines; white Gaussian noise reduction; Additive noise; Analysis of variance; Filters; Gaussian noise; Noise reduction; Speckle; Support vector machine classification; Support vector machines; Wavelet analysis; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nonlinear Signal and Image Processing, 2005. NSIP 2005. Abstracts. IEEE-Eurasip
  • Conference_Location
    Sapporo
  • Print_ISBN
    0-7803-9064-4
  • Type

    conf

  • DOI
    10.1109/NSIP.2005.1502256
  • Filename
    1502256