DocumentCode
3591663
Title
Automated segmentation of SAS images using the mean - standard deviation plane for the detection of underwater mines
Author
Maussang, FrCx00E9;d?©ric ; Chanussot, Jocelyn ; H?©tet, Alain
Author_Institution
Lab. des Images et des Signaux, Domaine Univ., St. Martin d´´Heres, France
Volume
4
fYear
2003
Firstpage
2155
Abstract
A segmentation method of synthetic aperture sonar (SAS) images is presented, in order to highlight some characteristics (number, position, shape, ...) of underwater mines echoes. This segmentation method is based on statistical characteristics of the sonar images, highlighted by the mean -standard deviation plane. It is automated by using an entropy criterion.
Keywords
geophysical prospecting; geophysical signal processing; image segmentation; military systems; oceanographic techniques; sonar imaging; statistical analysis; synthetic aperture sonar; automated segmentation; entropy criterion; image segmentation; mean standard deviation plane; statistical analysis; synthetic aperture sonar images; underwater mines echoes; Amplitude estimation; Dissolved gas analysis; Equations; Image resolution; Image segmentation; Shape; Signal resolution; Speckle; Synthetic aperture sonar; Underwater tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
OCEANS 2003. Proceedings
Print_ISBN
0-933957-30-0
Type
conf
DOI
10.1109/OCEANS.2003.178236
Filename
1282810
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