IDEAS home Printed from https://ideas.repec.org/a/igg/jismd0/v8y2017i2p1-29.html
   My bibliography  Save this article

Performance Assessment of Edge Preserving Filters

Author

Listed:
  • Kamireddy Rasool Reddy

    (JNTU Kakinada, Kakinada, India)

  • Madhava Rao Ch

    (Sir C.R. Reddy College of Engineering, Vijayawada, India)

  • Nagi Reddy Kalikiri

    (NBKR Institute of Science and Technology, Vidyanagar, India)

Abstract

Denoising is one of the important aspects in image processing applications. Denoising is the process of eliminating the noise from the noisy image. In most cases, noise accumulates at the edges. So that prevention of noise at edges is one of the most prominent problem. There are numerous edge preserving approaches available to reduce the noise at edges in that Gaussian filter, bilateral filter and non-local means filtering are the popular approaches but in these approaches denoised image suffer from blurring. To overcome these problems, in this article a Gaussian/bilateral filtering (G/BF) with a wavelet thresholding approach is proposed for better image denoising. The performance of the proposed work is compared with some edge-preserving filter algorithms such as a bilateral filter and the Non-Local Means Filter, in terms that objectively assess quality. From the simulation results, it is found that the performance of proposed method is superior to the bilateral filter and the Non-Local Means Filter.

Suggested Citation

  • Kamireddy Rasool Reddy & Madhava Rao Ch & Nagi Reddy Kalikiri, 2017. "Performance Assessment of Edge Preserving Filters," International Journal of Information System Modeling and Design (IJISMD), IGI Global, vol. 8(2), pages 1-29, April.
  • Handle: RePEc:igg:jismd0:v:8:y:2017:i:2:p:1-29
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJISMD.2017040101
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ramshani, Mohammad & Li, Xueping & Khojandi, Anahita & Omitaomu, Olufemi, 2020. "An agent-based approach to study the diffusion rate and the effect of policies on joint placement of photovoltaic panels and green roof under climate change uncertainty," Applied Energy, Elsevier, vol. 261(C).
    2. Maddalena Honorati & Sara Johansson de Silva & Natalia Millan & Florentin Kerschbaumer, 2019. "Work for a Better Future in Armenia," World Bank Publications - Reports 34412, The World Bank Group.

    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:igg:jismd0:v:8:y:2017:i:2:p:1-29. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.