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An Identification Approach to Image Deblurring
KTH.
2016 (English)In: PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016 / [ed] Chen, J Zhao, Q, IEEE Computer Society, 2016, p. 235-241Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we present a new method of reconstructing an image that undergoes a spatially invariant blurring process and is corrupted by noise. The methodology is based on a theory of multidimensional moment problems with rationality constraints. This can be seen as generalized spectral estimation with a finiteness condition, which in turn can be considered a problem in system identification. With noise it becomes an ill-posed deconvolution problem and needs regularization. A Newton solver is developed, and the algorithm is tested on two images under different boundary conditions. These preliminary results show that the proposed method could be a viable alternative to regularized least squares for image deblurring, although more work is needed to perfect the method.

Place, publisher, year, edition, pages
IEEE Computer Society, 2016. p. 235-241
Series
Chinese Control Conference, ISSN 2161-2927
Keywords [en]
Multidimensional moment problem, Rationality constraints, Image deblurring, Deconvolution, Convex optimization
National Category
Physical Sciences
Identifiers
URN: urn:nbn:se:kth:diva-204151DOI: 10.1109/ChiCC.2016.7553089ISI: 000388809500034Scopus ID: 2-s2.0-84987899029ISBN: 9789881563910 (print)OAI: oai:DiVA.org:kth-204151DiVA, id: diva2:1084752
Conference
35th Chinese Control Conference (CCC), JUL 27-29, 2016, Chengdu, PEOPLES R CHINA
Note

QC 20170327

Available from: 2017-03-27 Created: 2017-03-27 Last updated: 2017-05-11Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
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  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • asciidoc
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