Empirical Inference
Technical Report
2009
Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution
PDF
Empirical Inference
Empirical Inference
Ultimately being motivated by facilitating space-variant blind deconvolution, we present a class of linear transformations, that are expressive enough for space-variant filters, but at the same time especially designed for efficient matrix-vector-multiplications. Successful results on astronomical imaging through atmospheric turbulences and on noisy magnetic resonance images of constantly moving objects demonstrate the practical significance of our approach.
| Author(s): | Hirsch, M. and Sra, S. and Schölkopf, B. and Harmeling, S. |
| Links: | |
| Number (issue): | 188 |
| Year: | 2009 |
| Month: | November |
| Day: | 0 |
| BibTeX Type: | Technical Report (techreport) |
| Digital: | 0 |
| Electronic Archiving: | grant_archive |
| Institution: | Max Planck Institute for Biological Cybernetics, Tübingen, Germany |
| Organization: | Max-Planck-Gesellschaft |
| School: | Biologische Kybernetik |
BibTeX
@techreport{6328,
title = {Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution},
abstract = {Ultimately being motivated by facilitating space-variant blind deconvolution, we present a class of linear transformations, that are expressive enough for space-variant filters, but at the same time especially designed for efficient matrix-vector-multiplications. Successful results on astronomical imaging through atmospheric turbulences and on noisy magnetic resonance images of constantly moving objects demonstrate the practical significance of our approach.},
number = {188},
organization = {Max-Planck-Gesellschaft},
institution = {Max Planck Institute for Biological Cybernetics, Tübingen, Germany},
school = {Biologische Kybernetik},
month = nov,
year = {2009},
author = {Hirsch, M. and Sra, S. and Sch{\"o}lkopf, B. and Harmeling, S.},
month_numeric = {11}
}