Automated segmentation of SAS images using the mean - standard deviation plane for the detection of underwater mines
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.