• English
    • العربية
  • العربية
  • Login
  • QU
  • QU Library
  •  Home
  • Communities & Collections
  • Help
    • Item Submission
    • Publisher policies
    • User guides
    • FAQs
  • About QSpace
    • Vision & Mission
View Item 
  •   Qatar University Digital Hub
  • Qatar University Institutional Repository
  • Academic
  • Faculty Contributions
  • College of Engineering
  • Computer Science & Engineering
  • View Item
  • Qatar University Digital Hub
  • Qatar University Institutional Repository
  • Academic
  • Faculty Contributions
  • College of Engineering
  • Computer Science & Engineering
  • View Item
  •      
  •  
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Total Variation for Image Denoising Based on a Novel Smart Edge Detector: An Application to Medical Images

    Thumbnail
    Date
    2019
    Author
    Ben Said, Ahmed
    Hadjidj , Rachid
    Foufou, Sebti
    Metadata
    Show full item record
    Abstract
    In medical imaging applications, diagnosis relies essentially on good quality images. Edges play a crucial role in identifying features useful to reach accurate conclusions. However, noise can compromise this task as it degrades image information by altering important features and adding new artifacts rendering images non-diagnosable. In this paper, we propose a novel denoising technique based on the total variation method with an emphasis on edge preservation. Image denoising techniques such as the Rudin - Osher - Fatemi model which are guided by gradient regularizer are generally accompanied with staircasing effect and loss of details. To overcome these issues, our technique incorporates in the model functional, a novel edge detector derived from fuzzy complement, non-local mean filter and structure tensor. This procedure offers more control over the regularization, allowing more denoising in smooth regions and less denoising when processing edge regions. Experimental results on synthetic images demonstrate the ability of the proposed edge detector to determine edges with high accuracy. Furthermore, denoising experiments conducted on CT scan images and comparison with other denoising methods show the outperformance of the proposed denoising method.
    DOI/handle
    http://dx.doi.org/10.1007/s10851-018-0829-6
    http://hdl.handle.net/10576/14920
    Collections
    • Computer Science & Engineering [‎2429‎ items ]

    entitlement


    Qatar University Digital Hub is a digital collection operated and maintained by the Qatar University Library and supported by the ITS department

    Contact Us | Send Feedback
    Contact Us | Send Feedback | QU

     

     

    Home

    Submit your QU affiliated work

    Browse

    All of Digital Hub
      Communities & Collections Publication Date Author Title Subject Type Language Publisher
    This Collection
      Publication Date Author Title Subject Type Language Publisher

    My Account

    Login

    Statistics

    View Usage Statistics

    About QSpace

    Vision & Mission

    Help

    Item Submission Publisher policiesUser guides FAQs

    Qatar University Digital Hub is a digital collection operated and maintained by the Qatar University Library and supported by the ITS department

    Contact Us | Send Feedback
    Contact Us | Send Feedback | QU

     

     

    Video