From statistical detection to decision fusion : detection of underwater mines in high resolution SAS images
| Autor: | M. Amate, F. Maussang, Jocelyn Chanussot, Michèle Rombaut |
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| Přispěvatelé: | Télécom Bretagne, Bibliothèque, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (UMR 3192) (Lab-STICC), Université européenne de Bretagne - European University of Brittany (UEB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), GIPSA - Signal Images Physique (GIPSA-SIGMAPHY), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), GIPSA - Géométrie, Perception, Images, Geste (GIPSA-GPIG), Groupe d'Etudes Sous-Marines de l'Atlantique (DGA/DET/GESMA), DGA, Sergio Rui Silva, Département Image et Traitement Information (ITI), Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT), Groupe d'études sous-marines de l'atlantique (DGA) (GESMA), ROMBAUT, Michèle |
| Jazyk: | angličtina |
| Rok vydání: | 2009 |
| Předmět: |
Synthetic aperture radar
Engineering Similarity (geometry) [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing 02 engineering and technology 01 natural sciences Sonar [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Shadow Underwater acoustics 0202 electrical engineering electronic engineering information engineering Synthetic aperture sonar Computer vision 14. Life underwater 0105 earth and related environmental sciences [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing Data fusion process 010505 oceanography business.industry 020206 networking & telecommunications Object (computer science) Demining Sonar image processing Artificial intelligence business [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing Statistical method |
| Zdroj: | Advances in Sonar Technology Sergio Rui Silva,. Advances in Sonar Technology, IN-TECH (Open Acces Book), pp.111-150, 2009 Advances in Sonar Technology, edited by Sergio Rui Silva Advances in Sonar Technology, edited by Sergio Rui Silva, In-Tech, pp.111-150, 2009, 978-3-902613-48-6 |
| Popis: | Among all the applications proposed by sonar systems is underwater demining. Indeed, even if the problem is less exposed than the 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 (Milisavljeviþ 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 speckle 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 underwater 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 the 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. Starting from a synthetic aperture image, a complete detection and classification process would be composed of three main parts as follows: 1. Pixel level: the decision consists in deciding whether a pixel belongs to an object or to the background. 2. Object level: the decision concerns the segmented object which is real or not: are these objects interesting (mines) or simple rocks, wastes? Shape parameters (size, ) and position information can be us ed to answer this question. 3. Classification of object: the decision concerns the type of object and its identification (type of mine). This chapter deals with the first step of this proc ess. The goal is to evaluate a confidence that a pixel belongs to a sought object or to the seabed. In the following, considering the object |
| Databáze: | OpenAIRE |
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