Abstract
In [2], Chambolle proposed an algorithm for minimizing the total variation of an image. In this short note, based on the theory on semismooth operators, we study semismooth Newton's methods for total variation minimization. The convergence and numerical results are also presented to show the effectiveness of the proposed algorithms.
Original language | English |
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Pages (from-to) | 265-276 |
Number of pages | 12 |
Journal | Journal of Mathematical Imaging and Vision |
Volume | 27 |
Issue number | 3 |
DOIs | |
Publication status | Published - Apr 2007 |
Scopus Subject Areas
- Statistics and Probability
- Modelling and Simulation
- Condensed Matter Physics
- Computer Vision and Pattern Recognition
- Geometry and Topology
- Applied Mathematics
User-Defined Keywords
- Denoising
- Regularization
- Semismooth Newton's methods
- Total variation