• DocumentCode
    230178
  • Title

    A HMMF filter for removal of noise from digital images

  • Author

    Ilango, Gnanambal ; Marudhachalam, R.

  • Author_Institution
    Dept. of Math., Gov. Arts Coll., Coimbatore, India
  • fYear
    2014
  • fDate
    24-26 June 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In recent years, technological development has significantly improved in analyzing digital images. Noise reduction is an important operation in image processing. Removing impulse noise from digital image is a very active research area in digital image processing. This paper proposes a new non linear hybrid filtering technique which is the hybridization of hybrid max filter and hybrid min filter (HMMF) for the removal of impulse noise from digital images. Experimental results show the proposed method is very effective to filter salt-and-pepper noise. The measurement of noise reduction is difficult and there is no unique algorithm available to measure noise reduction of digital images. So the quality of the noise reduction in images is measured by the statistical quantity measures: Root Mean Square Error (RMSE) and Peak Signal-to-Noise Ratio (PSNR). The performance of this filter on images tainted with different noises of various noise levels is compared with Wiener filtering technique.
  • Keywords
    Wiener filters; filtering theory; image denoising; mean square error methods; nonlinear filters; statistical analysis; HMMF filter; PSNR; RMSE; Wiener filtering technique; digital images; hybrid max filter; hybrid min filter; image processing; noise reduction; noise removal; nonlinear hybrid filtering; peak signal-to-noise ratio; root mean square error; salt-and-pepper noise; statistical quantity measures; Digital images; Gaussian noise; Hidden Markov models; Image processing; PSNR; Speckle;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Norbert Wiener in the 21st Century (21CW), 2014 IEEE Conference on
  • Conference_Location
    Boston, MA
  • Type

    conf

  • DOI
    10.1109/NORBERT.2014.6893919
  • Filename
    6893919