TAILIEUCHUNG - Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010, Article

Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010, Article ID 205095, 13 pages doi: Review Article High-Resolution Sonars: What Resolution Do We Need for Target Recognition? Yan Pailhas, Yvan Petillot, and Chris Capus School of Electrical and Physical Science, Oceans Systems Laboratory, Heriot Watt University, Edinburgh EH14 4AS, Scotland, UK Correspondence should be addressed to Yan Pailhas, Received 23 December 2009; Revised 28 July 2010; Accepted 1 December 2010 Academic Editor: Yingzi Du Copyright © 2010 Yan Pailhas et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution,. | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 205095 13 pages doi 2010 205095 Review Article High-Resolution Sonars What Resolution Do We Need for Target Recognition Yan Pailhas Yvan Petillot and Chris Capus School of Electrical and Physical Science Oceans Systems Laboratory Heriot Watt University Edinburgh EH14 4AS Scotland UK Correspondence should be addressed to Yan Pailhas Received 23 December 2009 Revised 28 July 2010 Accepted 1 December 2010 Academic Editor Yingzi Du Copyright 2010 Yan Pailhas et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Target recognition in sonar imagery has long been an active research area in the maritime domain especially in the mine-counter measure context. Recently it has received even more attention as new sensors with increased resolution have been developed new threats to critical maritime assets and a new paradigm for target recognition based on autonomous platforms have emerged. With the recent introduction of Synthetic Aperture Sonar systems and high-frequency sonars sonar resolution has dramatically increased and noise levels decreased. Sonar images are distance images but at high resolution they tend to appear visually as optical images. Traditionally algorithms have been developed specifically for imaging sonars because of their limited resolution and high noise levels. With high-resolution sonars algorithms developed in the image processing field for natural images become applicable. However the lack of large datasets has hampered the development of such algorithms. Here we present a fast and realistic sonar simulator enabling development and evaluation of such algorithms. We develop a classifier and then analyse its performances using our simulated synthetic sonar images.

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