• DocumentCode
    238599
  • Title

    MAP-MRF approach for image denoising

  • Author

    Aravind, B.N. ; Suresh, K.V.

  • Author_Institution
    Dept. of Electron. & Commun. Eng., Kalpataru Inst. of Technol., Tiptur, India
  • fYear
    2014
  • fDate
    27-29 Nov. 2014
  • Firstpage
    923
  • Lastpage
    927
  • Abstract
    Digital images gets degraded due to several reasons. The aim of denoising involves the restoration of signal to yield visually good quality representation. In this paper, we are referring to an image corrupted by additive Gaussian noise. The image is modeled as MRF and maximum-a-posteriori (MAP) estimate is obtained using graduated non-convexity technique. Results suggest that the proposed technique yields better compared to other techniques.
  • Keywords
    Gaussian noise; image denoising; image representation; maximum likelihood estimation; MRF; additive Gaussian noise; digital images; graduated nonconvexity technique; image corruption; image denoising; image quality; image representation; maximum-a-posteriori estimate; signal restoration; Filtering; Image restoration; Noise; Noise measurement; Wiener filters; Discontinuity adaptive; MAP estimate; MRF; image denoising;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Contemporary Computing and Informatics (IC3I), 2014 International Conference on
  • Conference_Location
    Mysore
  • Type

    conf

  • DOI
    10.1109/IC3I.2014.7019648
  • Filename
    7019648
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=238599