Sigmoidal weighted vector directional filter

Authors:
Rastislav Lukac;Bogdan Smolka;Konstantinos N. Plataniotis;Anastasios N. Venetsanopoulos
Affiliations:
Slovak Image Processing Center, Dobsina, Slovak Republic;Department of Automatic Control, Silesian University of Technology, Gliwice, Poland;Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada;Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada
Venue:
ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
Year:
2003

Citing 3
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Abstract

In this paper, we provide and analyze a sigmoidal optimization of a recently developed class of weighted vector directional filters (WVDFs) outputting the input multichannel sample associated with the minimum sum of weighted angular distances to other input samples. Because the WVDFs can perform a number of smoothing operations in dependence on the weight coefficients, the aim of this paper is to adapt the WVDF behavior to statistical properties of noise and original color image. The filtering results and the complete analysis of the sigmoidal function based WVDF optimization are also provided.