Abstract
Mean curvature-based energy minimization denoising model by Zhu and Chan offers one approach for restoring both smooth (no edges) and non-smooth (with edges) images. The resulting fourth-order partial differential equations arising from minimization of this model is non-trivial to solve due to appearance of a high nonlinearity and stiffness term, because simple alternative methods such as the fixed point method and the primal dual method do not work. In this paper, we first present a relaxed fixed point method for solving such equations and further to combine with a homotopy algorithm to achieve fast convergence. Numerical experiments show that our method is able to maintain all important information in the image, and at the same time to filter out noise.
| Original language | English |
|---|---|
| Pages (from-to) | 274-285 |
| Number of pages | 12 |
| Journal | Optimization Methods and Software |
| Volume | 29 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 4 Mar 2014 |
Funding
The research was supported by the Fundamental Research Funds for the Central Universities (Jdzd12009), the natural science foundation of Hunan Province (13JJB014) and the National Natural Science Foundation of China (11171051) and (11101186).
Keywords
- homotopy method
- image denoising
- mean curvature model
- relaxed fixed point method
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