IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v339y2018icp308-322.html
   My bibliography  Save this article

Efficient computations for generalized Zernike moments and image recovery

Author

Listed:
  • Deng, An-Wen
  • Gwo, Chih-Ying

Abstract

Zernike moments are a set of orthogonal moments which have been successfully applied in the fields of image processing and pattern recognition. An innovative calculation method for Zernike moments, named generalized Zernike moments, is presented in this study. The generalized Zernike moment is a variant of Zernike moment. In this paper, we are proposing methods to calculate high-order generalized Zernike moments. Two kinds of recurrence for calculating generalized Zernike moments were introduced with rigorous proofs. Through the usage of the symmetries operated by the Dihedral group of order eight, the proposed method is fast and stable. The experimental results show that of the proposed method took 4.206s to compute the top 500-order generalized Zernike moments of an image with 512 by 512 pixels. Furthermore, by choosing the extra parameter α in the recurrence, the method enhanced the accuracy remarkably compared to the regular Zernike moments. Its normalized mean square error is 0.00144067 when α was set to 66 and the top 500-order moments were used to reconstruct the image. This error is 40.47% smaller than the one obtained by using the regular Zernike moments.

Suggested Citation

  • Deng, An-Wen & Gwo, Chih-Ying, 2018. "Efficient computations for generalized Zernike moments and image recovery," Applied Mathematics and Computation, Elsevier, vol. 339(C), pages 308-322.
  • Handle: RePEc:eee:apmaco:v:339:y:2018:i:c:p:308-322
    DOI: 10.1016/j.amc.2018.07.029
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300318305873
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2018.07.029?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:eee:apmaco:v:339:y:2018:i:c:p:308-322. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.