From statistical detection to decision fusion : detection of underwater mines in high resolution SAS images

Frederic Maussang (1) , Jocelyn Chanussot (2) , Michèle Rombaut (3) , Maud Amate (4)

1 ITI - Département Image et Traitement Information
2 GIPSA-SIGMAPHY - GIPSA - Signal Images Physique
3 GIPSA-GPIG - GIPSA - Géométrie, Perception, Images, Geste
4 GESMA - Groupe d'études sous-marines de l'atlantique (DGA)

Among all the applications proposed by sona r systems is underwater demining. Indeed, even if the problem is less exposed than th e terrestrial equivalent, the presence of underwater mines in waters near the coast an d particularly the harbours provoke accidents and victims in fishing and trade activiti es, even a long time after conflicts. As for terrestrial demining (Milisavljevi ć et al ., 2008), detection and classification of various types of underwater mines is cu rrently a crucial strategic task (U.S. Department of the Navy, 2000). Over the past decade, synthetic aperture sonar (SAS) has been increasingly used in seabed imaging, providing high-resolution images (Hayes & Gough, 1999). However, as with any active coherent imaging system, the speckl e constructs images with a strong granular aspect that can seriously handicap the interpre tation of the data (Abbot & Thurstone, 1979). Many approaches have been proposed in un derwater mine detection and classification using sonar images. Most of them use the charac teristics of the shadows cast by the objects on the seabed (Mignotte et al., 1997). These methods fail in case of buried objects, since no shadow is cast. That is why this last case has been less studied. In such cases, the echoes (high-intensity reflection of the wave on th e objects) are the only hint suggesting the presence of the objects. Their small size, even in SAS imaging, and the similarity of their amplitude with the background make the detection more complex.

Mots clés: Sonar image processing; Underwater acoustics; Statistical method; Data fusion process; Synthetic aperture sonar

Domaines: Traitement du signal et de l'image [eess.SP]

Frederic Maussang, Jocelyn Chanussot, Michèle Rombaut, Maud Amate. From statistical detection to decision fusion : detection of underwater mines in high resolution SAS images. Advances in Sonar Technology, edited by Sergio Rui Silva, In-Tech, pp.111 - 150, 2009, 978-3-902613-48-6. ⟨hal-02118475⟩