Synthetic Aperture Sonar (SAS) imagery is largely used in detection, location, and classification of underwater mines laying 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 matched filtering. This enables the precise location of the objects. This method is tested on real SAS data containing both underwater mines laying on the seabed and buried objects.
