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

Received: 18 March 2002

Published: 13 March 2003


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.


impulse burst removalburst modelsoft morphological filterstraining-based optimization

Authors’ Affiliations

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


© Copyright © 2003 Hindawi Publishing Corporation 2003