Name
Abstract | ||
|---|---|---|
Blind image deconvolution is required in many applications of microscopy imaging, remote sensing, and astronomical imaging. Unfortunately in a single-channel framework, serious conceptual and numerical problems are often encountered. Very recently, an eigenvector-based method (EVAM) was proposed for a multichannel framework which determines perfectly convolution masks in a noise-free environment if channel disparity, called co-primeness, is satisfied. We propose a novel iterative algorithm based on recent anisotropic denoising techniques of total variation and a Mumford-Shah functional with the EVAM restoration condition included. A linearization scheme of half-quadratic regularization together with a cell-centered finite difference discretization scheme is used in the algorithm and provides a unified approach to the solution of total variation or Mumford-Shah. The algorithm performs well even on very noisy images and does not require an exact estimation of mask orders. We demonstrate capabilities of the algorithm on synthetic data. Finally, the algorithm is applied to defocused images taken with a digital camera and to data from astronomical ground-based observations of the Sun. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/TIP.2003.815260 | IEEE Transactions on Image Processing |
Keywords | DocType | Volume |
multichannel blind iterative image,total vari- ation,half-quadratic regularization,single-channel framework,index termsó multichannel blind deconvolution,evam restoration condition,mumford-shah functional,astronomical ground-based observation,total variation,synthetic data,microscopy imaging,subspace methods,linearization scheme,novel iterative algorithm,conjugate gradient,astronomical imaging,multichannel framework,eigenvectors,deconvolution,finite difference,image restoration,iterative algorithm,indexation,iterative methods,convolution,finite difference methods,satisfiability,remote sensing,parameter estimation,blind deconvolution | Journal | 12 |
Issue | ISSN | Citations |
9 | 1057-7149 | 33 |
PageRank | References | Authors |
1.81 | 18 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Filip Sroubek | 1 | 149 | 7.80 |
| J. Flusser | 2 | 398 | 25.42 |