Open Access

Removing Impulse Bursts from Images by Training-Based Filtering

  • Pertti Koivisto1, 2Email author,
  • Jaakko Astola2,
  • Vladimir Lukin3,
  • Vladimir Melnik2 and
  • Oleg Tsymbal3
EURASIP Journal on Advances in Signal Processing20032003:472580

DOI: 10.1155/S1110865703211045

Received: 18 March 2002

Published: 13 March 2003

Abstract

The characteristics of impulse bursts in remote sensing images are analyzed and a model for this noise is proposed. The model also takes into consideration other noise types, for example, the multiplicative noise present in radar images. As a case study, soft morphological filters utilizing a training-based optimization scheme are used for the noise removal. Different approaches for the training are discussed. It is shown that these techniques can provide an effective removal of impulse bursts. At the same time, other noise types in images, for example, the multiplicative noise, can be suppressed without compromising good edge and detail preservation. Numerical simulation results, as well as examples of real remote sensing images, are presented.

Keywords

impulse burst removal burst model soft morphological filters training-based optimization

Authors’ Affiliations

(1)
Department of Mathematics, Statistics, and Philosophy, University of Tampere
(2)
Institute of Signal Processing, Tampere University of Technology
(3)
Department of Receivers, Transmitters, and Signal Processing, National Aerospace University, (Kharkov Aviation Institute)

Copyright

© Copyright © 2003 Hindawi Publishing Corporation 2003