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2006

Channel Smoothing: Efficient Robust Smoothing of Low-Level Signal Features

9 years 15 hour ago
Channel Smoothing: Efficient Robust Smoothing of Low-Level Signal Features
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, ...
Michael Felsberg, Per-Erik Forssén, Hanno S
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2006
Where PAMI
Authors Michael Felsberg, Per-Erik Forssén, Hanno Scharr
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