Bayesian data fusion of multiview synthetic aperture sonar imagery for seabed classification

IEEE Transactions on Image Processing

Volumn 18, Issue 6, 2009, Pages 1239-1254

  Williams, David P ^a  

^a NATO UNDERSEA RESEARCH CENTRE   (Italy)

Author keywords

Bayesian data fusion; Gaussian mixture models (GMMs); Multiview data; Seabed classification; Seabed segmentation; Synthetic aperture sonar (SAS)

Indexed keywords

BAYESIAN DATA FUSION; GAUSSIAN MIXTURE MODELS (GMMS); MULTIVIEW DATA; SEABED CLASSIFICATION; SEABED SEGMENTATION;

BAYESIAN NETWORKS; BLIND SOURCE SEPARATION; COMMUNICATION CHANNELS (INFORMATION THEORY); DATA FUSION; EDUCATION; IMAGE CLASSIFICATION; IMAGING SYSTEMS; INFORMATION FUSION; MIXTURES; OBJECT RECOGNITION; PHOTOACOUSTIC EFFECT; PROBABILITY; SONAR; SYNTHETIC APERTURE SONAR; SYNTHETIC APERTURES; UNDERWATER ACOUSTICS;

CLASSIFICATION (OF INFORMATION);

EID: 67349288064     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2009.2017161     Document Type: Article

References (19)

1. Y. Petillot, S. Reed, and E. Coiras, "A framework for evaluating underwater mine detection and classification algorithms using augmented reality," presented at the UDT Conf., 2006.
2. D. MacKay, "Information-based objective functions for active data selection," Neural Comput., vol. 4, no. 4, pp. 590-604, Jul. 1992.
3. Z. Reut, N. Pace, and M. Heaton, "Computer classification of seabeds by sonar," Nature, no. 314, pp. 426-428, 1985.
4. N. Pace and H. Gao, "Swathe seabed classification," IEEE J. Ocean Eng., vol. 13, no. 2, pp. 83-90, Apr. 1988.
5. B. Dasarathy and E. Holder, "Image characterizations based on joint gray-level run-length distributions," Pattern Recognit. Lett., vol. 12, no. 8, pp. 497-502, 1991.
6. D. Tamsett, "Seabed characterisation and classification from the power spectra of sidescan sonar data," Marine Geophys. Res., vol. 15, no. 1, pp. 43-64, 1993.
7. D. Carmichael, L. Linnett, S. Clarke, and B. Calder, "Seabed classification through multifractal analysis of sidescan sonar imagery," IEE Radar, Sonar, Navig., vol. 143, no. 3, pp. 140-148, June 1996.
8. D. Kerneis and B. Zerr, "Multisensor fusion for seabed classification," in Proc. MTS/IEEE OCEANS, 2005, pp. 815-820.
9. S. Reed, I. T. Ruiz, C. Capus, and Y. Petillot, "The fusion of large scale classified sidescan sonar image mosaics," IEEE Trans. Image Process., vol. 15, no. 7, pp. 2049-2060, Jul. 2006.
10. E. Coiras, V. Myers, and B. Evans, "Reliable seabed characterization for MCM operations," presented at the MTS/IEEE OCEANS, Vancouver, BC, Canada, 2007.
11. A. Dempster, N. Laird, and D. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J. Roy. Statist. Soc. B, vol. 39, pp. 1-38, 1977.
12. N. Nasios and A. Bors, "Variational expectation-maximization training for Gaussian networks," in Proc. IEEE Workshop on Neural Networks for Signal Processing, 2003, pp. 339-348.
13. M. Beal and Z. Ghahramani, "The variational Bayesian EM algorithm for incomplete data: Application to scoring graphical model structures," Bayesian Statist., vol. 7, pp. 453-464, 2003.
14. M. Beal, "Variational Algorithms for Approximate Bayesian Inference," Ph.D. dissertation, Gatsby Computational Neuroscience Unit, University College London, 2003.
15. V. Fedorov, Theory of Optimal Experiments. New York: Academic, 1972.
16. T. Cover and J. Thomas, Elements of Information Theory. New York: Wiley, 1991.
17. S. Mallat, A Wavelet Tour of Signal Processing. New York: Academic, 1999.
18. J. Fawcett, A. Crawford, D. Hopkin, V. Myers, and B. Zerr, Computer-Aided Detection of Targets From the CITADEL Trial Klein Sonar Data, Defence R&D Canada-Atlantic, Tech. Rep. DRDC Atlantic TM2006-115, 2006.
19. R. Duda, P. Hart, and D. Stork, Pattern Classification, 2nd ed. New York: Wiley, 2001.