Projects per year
In this paper, motivated by approximating the Euler-Lagrange equation of the pth-order regularization for 0 < p ≤ 1, we propose a new regularization model with adaptive diffusivity for variational image denoising. The model is equipped with a regularization controller which is introduced to adaptively adjust the diffusivity from pixel to pixel according to the magnitude of image gradient. The associated energy functional is convex and thus the minimization problem can be efficiently solved using a modified split Bregman iterative scheme. A convergence analysis of the iterative scheme is established. Numerical experiments are performed to demonstrate the good performance of the proposed model. Comparisons with some other image denoising models are also made.
- Image denoising
- Split Bregman iteration
- Total variation
FingerprintDive into the research topics of 'A regularization model with adaptive diffusivity for variational image denoising'. Together they form a unique fingerprint.
- 1 Finished
On Efficient Numerical Methods for Simulating the Dynamics of Fluid-Structure Interaction Problems(2/2)
1/08/18 → 31/07/19