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 language | English |
|---|---|
| Pages (from-to) | 659-670 |
| Number of pages | 12 |
| Journal | Neurocomputing |
| Volume | 173 |
| DOIs | |
| State | Published - 15 Jan 2016 |
Keywords
- Impulse noise
- Mixed Gaussian impulse noise
- Noise indicator
- Nonlinear diffusion
- Regularized Perona-Malik diffusion
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