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Proceedings Paper

Modified vector sigma filter and its application to color and multichannel remote sensing radar image processing
Author(s): Andrei A. Kurekin; Vladimir V. Lukin; Alexander A. Zelensky; Jaakko T. Astola; Pertti T. Koivisto
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Paper Abstract

A novel algorithm based on the sigma filter for processing multicomponent images is proposed. The noise suppression ability of the proposed vector filtering algorithm is better than, e.g., that of the standard sigma filter. Moreover, the added modifications make the filter able to remove impulsive noise. The proposed vector filter takes into account the mutual correlation between image components and preserves object edges and fine details even when the contrasts of the component images of multichannel data are low. The comparative analysis of filter performance is done both visually and using several quantitative criteria. Both simulated and real color and multichannel radar images are studied. It is shown that the modified vector sigma filter outperforms many component and vector filters. Two modifications are considered -- for cases of additive and multiplicative noise. Examples of the filter performance for processing real images formed by multipolarization/multifrequency side-look aperture radars are presented.

Paper Details

Date Published: 18 October 1999
PDF: 12 pages
Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); doi: 10.1117/12.365854
Show Author Affiliations
Andrei A. Kurekin, Kharkov Aviation Institute (Ukraine)
Vladimir V. Lukin, Kharkov Aviation Institute (Ukraine)
Alexander A. Zelensky, Kharkov Aviation Institute (Ukraine)
Jaakko T. Astola, Tampere Univ. of Technology (Finland)
Pertti T. Koivisto, Tampere Univ. of Technology (Finland)

Published in SPIE Proceedings Vol. 3808:
Applications of Digital Image Processing XXII
Andrew G. Tescher, Editor(s)

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