DocumentCode
3346846
Title
On the use of higher order statistics in SAS imagery [synthetic aperture sonar]
Author
Maussang, F. ; Chanussot, J. ; Hétet, A.
Author_Institution
Lab. des Images et des Signaux, Domaine Univ., Saint-Martin-D´´Heres, France
Volume
5
fYear
2004
fDate
17-21 May 2004
Abstract
Synthetic aperture sonar (SAS) imagery is largely used in detection, location and classification of underwater mines laying on or buried in the sea bed. This paper proposes a detection method using higher order statistics (HOS) on SAS images. The proposed method can be divided into two steps. Firstly, the HOS (skewness and kurtosis) are locally estimated using a square sliding computation window. In a second step, the results are focused by a correlation process. This enables the precise location of the objects. This method is tested on real SAS data containing both underwater mines laying on the sea bed and buried objects.
Keywords
buried object detection; correlation methods; higher order statistics; image classification; object detection; sonar imaging; synthetic aperture sonar; HOS; SAS imagery; buried objects; correlation process; higher order statistics; kurtosis; mine classification; mine detection; mine location; sea bed buried mines; sea bed imagery; sea bed laying mines; skewness; square sliding computation window; synthetic aperture sonar; underwater mines; Buried object detection; Dissolved gas analysis; Focusing; Gaussian distribution; Higher order statistics; Noise level; Sea measurements; Synthetic aperture sonar; Testing; Underwater tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
ISSN
1520-6149
Print_ISBN
0-7803-8484-9
Type
conf
DOI
10.1109/ICASSP.2004.1327099
Filename
1327099
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