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Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution

2010

Conference Paper

ei


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.
Book Title: Proceedings of the 23rd IEEE Conference on Computer Vision and Pattern Recognition
Pages: 607-614
Year: 2010
Month: June
Day: 0
Publisher: IEEE

Department(s): Empirical Inference
Research Project(s): Computational Imaging
Bibtex Type: Conference Paper (inproceedings)

Address: Piscataway, NJ, USA
DOI: 10.1109/CVPR.2010.5540158
Event Name: CVPR 2010
Event Place: San Francisco, CA, USA
ISBN: 978-1-424-47029-7
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@inproceedings{6335,
  title = {Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution},
  author = {Hirsch, M. and Sra, S. and Sch{\"o}lkopf, B. and Harmeling, S.},
  booktitle = {Proceedings of the 23rd IEEE Conference on Computer Vision and Pattern Recognition},
  pages = {607-614},
  publisher = {IEEE},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Piscataway, NJ, USA},
  month = jun,
  year = {2010},
  month_numeric = {6}
}