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  Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution

Hirsch, M., Sra, S., Schölkopf, B., & Harmeling, S. (2010). Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution. In Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010) (pp. 607-614). Piscataway, NJ, USA: IEEE.

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Hirsch, M1, 2, Author           
Sra, S1, 2, Author           
Schölkopf, B1, 2, Author           
Harmeling, S1, 2, Author           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 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.

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 Dates: 2010-06
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1109/CVPR.2010.5540158
BibTex Citekey: 6335
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Title: Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010)
Place of Event: San Francisco, CA, USA
Start-/End Date: 2010-06-13 - 2010-06-18

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Title: Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010)
Source Genre: Proceedings
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Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 607 - 614 Identifier: ISBN: 978-1-424-47029-7