• DocumentCode
    3271643
  • Title

    Local weighted Gaussian curvature for image processing

  • Author

    Yuanhao Gong ; Sbalzarini, Ivo F.

  • Author_Institution
    Center of Syst. Biol., Max Planck Inst. of Mol. Cell Biol. & Genetics, Dresden, Germany
  • fYear
    2013
  • fDate
    15-18 Sept. 2013
  • Firstpage
    534
  • Lastpage
    538
  • Abstract
    We present a variational model with local weighted Gaussian curvature as regularizer. We show its convexity for an area-weight function and provide a closed-form solution for this case. The corresponding regularization coefficient has a theoretical bound. Moreover, we prove that the model is convex for a wide range of weight functions and show that it can be efficiently solved using splitting techniques. Finally, we demonstrate several applications of the model in image de-noising, smoothing, texture decomposition, image sharpening, and regularization-coefficient optimization.
  • Keywords
    Gaussian processes; convex programming; image denoising; image texture; smoothing methods; variational techniques; area-weight function; closed-form solution; convex model; image denoising; image processing; image sharpening; image smoothing; local weighted Gaussian curvature; regularization coefficient; regularization-coefficient optimization; splitting techniques; texture decomposition; variational model; weight functions; Approximation methods; Closed-form solutions; Computational modeling; Manganese; Mathematical model; Smoothing methods; TV; Gaussian curvature; convex model; image processing; regularization; variational form;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2013 20th IEEE International Conference on
  • Conference_Location
    Melbourne, VIC
  • Type

    conf

  • DOI
    10.1109/ICIP.2013.6738110
  • Filename
    6738110