IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/9205809.html
   My bibliography  Save this article

Total Bending Method for Piecewise Smoothing Image Denoising

Author

Listed:
  • Bibo Lu
  • Zhenzhen Huangfu
  • Rui Huang

Abstract

Since the seminar work by Rudin, Osher, and Fatami for total variation (TV) model, piecewise smoothing image is favored in a diversity of related fields. To recover a piecewise smoothing image, we propose a high order anisotropic geometrical model which we name total bending (TB) in a multiplicative strategy. TB model measures the bending degree of the image surface by approximating its second fundamental form. The analysis shows that TB is a rotation version of TV model in moving Frenet–Serret frame: TB norm measures the jumps along the normal direction in an adaptive local coordinate while TV measures the jumps along the vertical direction in a fixed Cartesian coordinate. TB reduces undesired staircase effect by recovering the horizontal and slope surface. The evolution diffusion of TB model inherits TV’s edge preserving ability. The experimental results show the performance of the proposed model quantitatively and visually.

Suggested Citation

  • Bibo Lu & Zhenzhen Huangfu & Rui Huang, 2019. "Total Bending Method for Piecewise Smoothing Image Denoising," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-14, May.
  • Handle: RePEc:hin:jnlmpe:9205809
    DOI: 10.1155/2019/9205809
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2019/9205809.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/MPE/2019/9205809.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2019/9205809?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:9205809. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.