IDEAS home Printed from https://ideas.repec.org/a/wly/jnlaaa/v2020y2020i1n7624829.html
   My bibliography  Save this article

Perona‐Malik Model with Diffusion Coefficient Depending on Fractional Gradient via Caputo‐Fabrizio Derivative

Author

Listed:
  • Gustavo Asumu Mboro Nchama
  • Angela Leon Mecias
  • Mariano Rodriguez Ricard

Abstract

The Perona‐Malik (PM) model is used successfully in image processing to eliminate noise while preserving edges; however, this model has a major drawback: it tends to make the image look blocky. This work proposes to modify the PM model by introducing the Caputo‐Fabrizio fractional gradient inside the diffusivity function. Experiments with natural images show that our model can suppress efficiently the blocky effect. Also, our model has good performance in visual quality, high peak signal‐to‐noise ratio (PSNR), and lower value of mean absolute error (MAE) and mean square error (MSE).

Suggested Citation

Handle: RePEc:wly:jnlaaa:v:2020:y:2020:i:1:n:7624829
DOI: 10.1155/2020/7624829
as

Download full text from publisher

File URL: https://doi.org/10.1155/2020/7624829
Download Restriction: no
File URL: https://libkey.io/10.1155/2020/7624829?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:wly:jnlaaa:v:2020:y:2020:i:1:n:7624829. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1155/4058 .

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.