TY  - JOUR
AU  - Felsberg, R. E.
AU  - Forssén, V. T.
AU  - Scharr, H.
TI  - Channel smoothing: Efficient robust smoothing of low-level signal features
JO  - IEEE transactions on pattern analysis and machine intelligence
VL  - 28
SN  - 0162-8828
CY  - New York, NY
PB  - IEEE
M1  - PreJuSER-47026
SP  - 209 - 222
PY  - 2006
N1  - Record converted from VDB: 12.11.2012
AB  - 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.
KW  - Algorithms
KW  - Artificial Intelligence
KW  - Data Compression: methods
KW  - Image Enhancement: methods
KW  - Image Interpretation, Computer-Assisted: methods
KW  - Numerical Analysis, Computer-Assisted
KW  - Pattern Recognition, Automated: methods
KW  - Signal Processing, Computer-Assisted
KW  - J (WoSType)
LB  - PUB:(DE-HGF)16
C6  - pmid:16468618
UR  - <Go to ISI:>//WOS:000233824500004
DO  - DOI:10.1109/TPAMI.2006.29
UR  - https://juser.fz-juelich.de/record/47026
ER  -