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A non-divergence diffusion equation for removing impulse noise and mixed Gaussian impulse noise

  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, a non-divergence diffusion equation consisting of an impulse noise indicator λ and a regularized Perona-Malik (RPM) diffusion operator is proposed for the removal of impulse noise. The impulse noise indicator λ is designed to keep values of noise-free pixels unaltered while the Gaussian kernel in the RPM operator makes the proposed equation insensitive to impulse noise. As a result, the proposed equation succeeds in noise suppression as well as edge preserving and shows better performance than state-of-the-art PDE-based methods and variational regularization methods. In addition, the numerical solution of the proposed equation has a certain asymptotic behavior: it converges to the solution we are interested in automatically. This property avoids the problem of choosing a stopping time in numerical experiments and allows us to continue removing impulse noise and mixed Gaussian impulse noise by using the proposed equation.

Original languageEnglish
Pages (from-to)659-670
Number of pages12
JournalNeurocomputing
Volume173
DOIs
StatePublished - 15 Jan 2016

Keywords

  • Impulse noise
  • Mixed Gaussian impulse noise
  • Noise indicator
  • Nonlinear diffusion
  • Regularized Perona-Malik diffusion

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