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Channel smoothing: Efficient robust smoothing of low-level signal features
Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Computer Vision.ORCID iD: 0000-0002-6096-3648
Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Computer Vision.ORCID iD: 0000-0002-5698-5983
IEEE Computer Society, Forschungszentrum Jülich GmbH, ICG-III, 52425 Jülich, Germany.
2006 (English)In: IEEE Transaction on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, E-ISSN 1939-3539, Vol. 28, no 2, 209-222 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, we present a new and efficient method to implement robust smoothing of low-level signal features: B-spline channel smoothing. This method consists of three steps: encoding of the signal features into channels, averaging of the channels, and decoding of the channels. We show that linear smoothing of channels is equivalent to robust smoothing of the signal features if we make use of quadratic B-splines to generate the channels. The linear decoding from B-spline channels allows the derivation of a robust error norm, which is very similar to Tukey's biweight error norm. We compare channel smoothing with three other robust smoothing techniques: nonlinear diffusion, bilateral filtering, and mean-shift filtering, both theoretically and on a 2D orientation-data smoothing task. Channel smoothing is found to be superior in four respects: It has a lower computational complexity, it is easy to implement, it chooses the global minimum error instead of the nearest local minimum, and it can also be used on nonlinear spaces, such as orientation space. © 2006 IEEE.

Place, publisher, year, edition, pages
2006. Vol. 28, no 2, 209-222 p.
Keyword [en]
B-spline, Bilateral filtering, Channel representation, Diffusion filtering, Mean-shift, Orientation smoothing, Robust smoothing
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-50049DOI: 10.1109/TPAMI.2006.29OAI: oai:DiVA.org:liu-50049DiVA: diva2:270945
Note
©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Michael Felsberg, P.-E. Forssen and H. Scharr, Channel smoothing: Efficient robust smoothing of low-level signal features, 2006, IEEE Transaction on Pattern Analysis and Machine Intelligence, (28), 2, 209-222. http://dx.doi.org/10.1109/TPAMI.2006.29 Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2017-12-12

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Felsberg, MichaelForssen, P.-E.

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