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B-Spline Channel Smoothing for Robust Estimation
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-6096-3648
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-5698-5983
n/a.
2004 (English)Report (Other academic)
Abstract [en]

In this paper we present a new method to implement a robust estimator: B-spline channel smoothing. We show that linear smoothing of channels is equivalent to a robust estimator, where we make use of the channel representation based upon quadratic B-splines. The linear decoding from B-spline channels allows to derive a robust error norm which is very similar to Tukey's biweight error norm. Using channel smoothing instead of iterative robust estimator implementations like non-linear diffusion, bilateral filtering, and mean-shift approaches is advantageous since channel smoothing is faster, it is easy to implement, it chooses the global minimum error instead of the nearest local minimum, and it can also be used on non-linear spaces, such as orientation space. As an application, we implemented orientation smoothing and compared it to the other three approaches.

Place, publisher, year, edition, pages
Linköping, Sweden: Linköping University, Department of Electrical Engineering , 2004. , 26 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2579
Keyword [en]
channel representation, diffusion filtering, bilateral
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-53346ISRN: LiTH-ISY-R-2579OAI: oai:DiVA.org:liu-53346DiVA: diva2:288549
Available from: 2010-01-21 Created: 2010-01-20 Last updated: 2016-05-04Bibliographically approved

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Felsberg, MichaelForssen, Per-Erik

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf