Abstract
Image restoration, i.e., the recovery of images that have been degraded by blur and noise, is a challenging inverse problem. A unified variational approach to edge-preserving image deconvolution and impulsive noise removal has recently been suggested by the authors and shown to be effective. It leads to a minimization problem that is iteratively solved by alternate minimization for both the recovered image and the discontinuity set. The variational formulation yields a nonlinear integro-differential equation. This equation was linearized by fixed point iteration. In this paper, we analyze and prove the convergence of the iterative method.
| Original language | English |
|---|---|
| Pages (from-to) | 983-994 |
| Number of pages | 12 |
| Journal | Multiscale Modeling and Simulation |
| Volume | 6 |
| Issue number | 3 |
| DOIs | |
| State | Published - Aug 2007 |
Keywords
- Convergence analysis
- Variational image deconvolution
Fingerprint
Dive into the research topics of 'Convergence of an iterative method for variational deconvolution and impulsive noise removal'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver