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.
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