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B-Spline Channel Smoothing for Robust Estimation

Felsberg, M., Forssén, P.-E., Scharr, H.
January 2004


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.


channel representation, diffusion filtering, bilateral

Bibtex entry

  author = 	 {Felsberg, M. and Forss{\'e}n, P.-E. and Scharr, H.},
  title = 	 {B-Spline Channel Smoothing for Robust Estimation},
  institution =  {Dept. EE, Link\"oping University},
  year = 	 {2004},
  number = 	 {LiTH-ISY-R-2579},
  address = 	 {SE-581 83 Link\"oping, Sweden},
  month = 	 {January}

Per-Erik Forssén

Per-Erik Forssén


Computer Vision Laboratory
Department of Electrical Engineering
Building B
Room 2D:521
SE-581 83 Linköping, Sweden
+46(0)13 285654

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Senast uppdaterad: 2023-09-06