• DocumentCode
    2964888
  • Title

    Image Enhancement Usingwavelet-Domain Mixture Models

  • Author

    Shi, Fei ; Selesnick, Ivan W. ; Guleryuz, Onur

  • Author_Institution
    Polytech. Univ., Brooklyn, NY
  • fYear
    2006
  • fDate
    24-27 Sept. 2006
  • Firstpage
    590
  • Lastpage
    595
  • Abstract
    We propose a non-linear mapping function for digital image enhancement in the wavelet domain, which amplifies mid-range coefficients more than small and large coefficients. We derive this function based on a statistical model of the wavelet coefficients. This three-component mixture model describes the coefficients in each subband as a mixture of small, medium, and large coefficients to which different amplification factors are assigned. The model parameters are estimated from each subband using the EM algorithm. The algorithm has a small number of user-specified parameters while can obtain good enhancement results
  • Keywords
    amplification; expectation-maximisation algorithm; image enhancement; statistical analysis; EM algorithm; amplification factors; digital image enhancement; expectation-maximization algorithm; nonlinear mapping function; statistical model; wavelet-domain mixture models; Boosting; Digital images; Frequency domain analysis; Gaussian distribution; Image enhancement; Laplace equations; Parameter estimation; Wavelet coefficients; Wavelet domain; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Signal Processing Workshop, 12th - Signal Processing Education Workshop, 4th
  • Conference_Location
    Teton National Park, WY
  • Print_ISBN
    1-4244-3534-3
  • Electronic_ISBN
    1-4244-0535-1
  • Type

    conf

  • DOI
    10.1109/DSPWS.2006.265492
  • Filename
    4041133