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
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;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
Print_ISBN :
0-7803-8484-9
DOI :
10.1109/ICASSP.2004.1327099