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SPECKLE FILTERING IN SAR IMAGES USING MORPHOLOGICAL FILTERS

M. Młynarczuk

First published: 2018-06-20https://doi.org/10.5593/sgem2018/2.3/s10.023View metrics

Abstract

During the satellite SAR (Synthetic Aperture Radar) data analysis it is highly important to remove all the noise components from the image. The most critical disturbance that affects radar images is speckle noise. Many different filtration methods to reduce this noise have been proposed in the literature up to now. This paper presents the results of SAR image filtration using the methods of mathematical morphology. During this work over 20 different morphological filters have been tested ? both classical ones (opening, closing, alternating filters, sequential alternating filters), and also less used morphological filters realized with using geodetic reconstruction. Different sizes of structural elements have been used. The tests have been done for TerraSAR-X SAR image acquired in the Staring Spotlight mode over the port in Singapore. For the analysis, the part of satellite radar image with a ship and surrounded sea surface was selected. Such scene is characterized by the homogeneity of the background (see) and sharp edges of the object (ship). The goal of the study was to check how each morphological filter deal both with equalizing the background and keeping the edges of the object. To study the homogeneity of the background, standard deviations of the selected parts of the see after filtration has been analyzed. The influence of the filtration on the edges has been assessed based on the analysis of the image profiles and sizes of morphological gradients on the edges of objects. Results show that the application of morphological operations can be very useful in SAR imagery filtration. By analyzing results of each filtration method it has been concluded that the best results have been generated by morphological filters that use reconstruction.

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Publication details

Title
SPECKLE FILTERING IN SAR IMAGES USING MORPHOLOGICAL FILTERS
Authors
M. Młynarczuk
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 18th International Multidisciplinary Scientific GeoConference SGEM2018, Informatics, Geoinformatics and Remote Sensing
Publisher
STEF92 Technology
Year
2018
Pages
175-182
SWS Citekey
Mlynarczuk201810175182
ISSN
1314-2704
ISBN
978-619-7408-41-6
Language
en
Publication type
Conference Paper
Keywords
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Number of times cited according to Crossref: 1

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