TAILIEUCHUNG - EURASIP Journal on Applied Signal Processing 2003:3, 223–237 c 2003 Hindawi Publishing
EURASIP Journal on Applied Signal Processing 2003:3, 223–237 c 2003 Hindawi Publishing Corporation Removing Impulse Bursts from Images by Training-Based Filtering Pertti Koivisto Department of Mathematics, Statistics, and Philosophy, University of Tampere, Finland Institute of Signal Processing, Tampere University of Technology, Tampere, Finland Email: Jaakko Astola Institute of Signal Processing, Tampere University of Technology, Tampere, Finland Email: Vladimir Lukin Department of Receivers, Transmitters, and Signal Processing, National Aerospace University (Kharkov Aviation Institute), Kharkov, Ukraine Email: lukin@ Vladimir Melnik Institute of Signal Processing, Tampere University of Technology, Tampere, Finland Email: Oleg Tsymbal Department of Receivers, Transmitters, and Signal Processing, National Aerospace University (Kharkov Aviation Institute), Kharkov, Ukraine Email:. | EURASIP Journal on Applied Signal Processing 2003 3 223-237 2003 Hindawi Publishing Corporation Removing Impulse Bursts from Images by Training-Based Filtering Pertti Koivisto Department of Mathematics Statistics and Philosophy University of Tampere Finland Institute of Signal Processing Tampere University of Technology Tampere Finland Email Jaakko Astola Institute of Signal Processing Tampere University of Technology Tampere Finland Email Vladimir Lukin Department of Receivers Transmitters and Signal Processing National Aerospace University Kharkov Aviation Institute Kharkov Ukraine Email lukin@ Vladimir Melnik Institute of Signal Processing Tampere University of Technology Tampere Finland Email Oleg Tsymbal Department of Receivers Transmitters and Signal Processing National Aerospace University Kharkov Aviation Institute Kharkov Ukraine Email dmb@ Received 18 March 2002 and in revised form 15 September 2002 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 and phrases impulse burst removal burst model soft morphological filters training-based optimization. 1. INTRODUCTION Remote sensing images are usually formed on board an aircraft or spaceborne carrier where sensors and .
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