Open Access

Generalized Selection Weighted Vector Filters

  • Rastislav Lukac1Email author,
  • Konstantinos N. Plataniotis1,
  • Bogdan Smolka2 and
  • Anastasios N. Venetsanopoulos1
EURASIP Journal on Advances in Signal Processing20042004:347160

DOI: 10.1155/S1110865704312126

Received: 21 July 2003

Published: 29 September 2004

Abstract

This paper introduces a class of nonlinear multichannel filters capable of removing impulsive noise in color images. The here-proposed generalized selection weighted vector filter class constitutes a powerful filtering framework for multichannel signal processing. Previously defined multichannel filters such as vector median filter, basic vector directional filter, directional-distance filter, weighted vector median filters, and weighted vector directional filters are treated from a global viewpoint using the proposed framework. Robust order-statistic concepts and increased degree of freedom in filter design make the proposed method attractive for a variety of applications. Introduced multichannel sigmoidal adaptation of the filter parameters and its modifications allow to accommodate the filter parameters to varying signal and noise statistics. Simulation studies reported in this paper indicate that the proposed filter class is computationally attractive, yields excellent performance, and is able to preserve fine details and color information while efficiently suppressing impulsive noise. This paper is an extended version of the paper by Lukac et al. presented at the 2003 IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP '03) in Grado, Italy.

Keywords

multichannel image processing color image processing nonlinear vector filtering order-statistic theory adaptive filter design noise removal

Authors’ Affiliations

(1)
The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto
(2)
Department of Automatic Control, Silesian University of Technology

Copyright

© Lukac et al. 2004