• DocumentCode
    2278345
  • Title

    Partial Differential Equation Model Method Based on Image Feature for Denoising

  • Author

    Zhang, Xiaohua ; Wang, Ran ; Jiao, L.C.

  • Author_Institution
    Key Lab. of Intell. Perception & Image Understanding of the Minist. of Educ. of China, Xidian Univ., Xi´´an, China
  • fYear
    2011
  • fDate
    10-12 Jan. 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    For the special different nature images, we could hardly find particularly desirable approach, and there always exist Gibbs-type artifacts in the results of most methods. A novel Partial Differential Equation (PDE) model is proposed based on image feature for images denoising. The PDE model is adaptive within each region according to the details of the image feature to adjust the size of the diffusion coefficient. So it can be disposed the high gradient noise at the same time better to retain the edge information. We also analyze the performance of the PDE model method. Numerical results show that our algorithm competes favorably with state of the-art TV projection methods to eliminate noise and reduce Gibbs-type artifacts.
  • Keywords
    diffusion; image denoising; partial differential equations; Gibbs type artifacts; Gibbs-type artifacts; PDE model; diffusion coefficient; gradient noise; image denoising; image feature; nature images; partial differential equation model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multi-Platform/Multi-Sensor Remote Sensing and Mapping (M2RSM), 2011 International Workshop on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4244-9402-6
  • Type

    conf

  • DOI
    10.1109/M2RSM.2011.5697408
  • Filename
    5697408