Abstract
In the underwater mine warfare context, potential threats are usually detected and classified by means of an Automatic Target Recognition (ATR) chain, especially in case of newly surveyed areas. However, if we can rely on a previously acquired sonar track, it is conceivable to directly compare such a track, said as reference, with a more recent one in order to detect seabed changes such as new objects lying on the seabed. To perform this change detection process, the very first step consists in geometrically aligning the reference and the repeated tracks. In this paper, we detail a block-matching approach using masked Fourier cross-correlation as a similarity metric, to carry out a fast elastic registration in a multi resolution framework. To improve the robustness of the algorithm, the resulting vector field is then filtered thanks to the navigation uncertainty, provided by the INS, along with an Inverse Distance Weighting estimate, to get rid of outliers.
The original version of this chapter was revised: For detailed information please see Erratum. The erratum to this chapter is available at https://doi.org/10.1007/978-3-319-70724-2_10
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
B.Ā Zerr, G.Ā Mailfert, A.Ā Bertholom, H.Ā Ayreault, Sidescan sonar image processing for auv navigation, in Oceans 2005-Europe, (vol.Ā 1), (June 2005), pp. 124ā130
P. King, B. Anstey, A. Vardy, Comparison of feature detection techniques for auv navigation along a trained route. Oceans-San Diego 2013, 1ā8 (2013)
P.Ā Vandrish, A.Ā Vardy, D.Ā Walker, O.Ā Dobre, Side-scan sonar image registration for auv navigation, in Underwater Technology (UT), 2011 IEEE Symposium on and 2011 Workshop on Scientific Use of Submarine Cables and Related Technologies (SSC), (April 2011), pp. 1ā7
L. Bernicola, D. Gueriot, J.-M. Le Caillec, A hybrid registration approach combining slam and elastic matching for automatic side-scan sonar mosaic. Oceans-St Johnās 2014, 1ā5 (2014)
I.Ā Leblond, Recalage PĆ long terme dāimages sonar par mise en correspondance de cartes de classification automatique des fonds, Ph.D. dissertation, (UniversitĆ© de Bretagne Occidentale, 2006)
C. Chailloux, J.-M. Le Caillec, D. Gueriot, B. Zerr, Intensity-based block matching algorithm for mosaicing sonar images. IEEE J. Ocean. Eng. 36(4), 627ā645 (2011)
J. Ferrand, N. Mandelert, Change detection for mcm survey mission, in International Conference on Detection and Classification of Underwater Targets (2012), pp. 193ā206
I.Ā Quidu, Incoherent change detection using amplitude sidescan sonar image, in ECUA 2012 (2013). http://dx.doi.org/10.1117/12.2053067
I.Ā Quidu, V.Ā Myers, Ć.Ā Midtgaard, R.Ā Hansen, Subpixel image registration for coherent change detection between two high resolution sonar passes, in iCoURSā12 (2012)
T. G-Michael, B.Ā Marchand, J.D. Tucker, D.D. Sternlicht, T.M. Marston, M.R. Azimi-Sadjadi, Automated change detection for synthetic aperture sonar, vol. 9072, (2014), pp. 907Ā 204ā907Ā 204ā11. http://dx.doi.org/10.1117/12.2053067
D.Ā Gueriot, E.Ā Maillard, J.-P. Kernin, Sonar image registration through symbolic matching: a fuzzy local transform approach using genetic algorithms, in OCEANSā96. MTS/IEEE. Prospects for the 21st Century. Conference Proceedings, vol.Ā 3, (Sep 1996), pp. 1324ā1329
I.Ā Barrodale, R.Ā Kuwahara, R.Ā Poeckert, D.Ā Skea, Side-scan sonar image processing using thin plate splines and control point matching. Numer. Algorithms 5(2), 85ā98 (1993). http://dx.doi.org/10.1007/BF02212041
S. Daniel, F. Le Leannec, C. Roux, B. Soliman, E. Maillard, Side-scan sonar image matching. IEEE J. Ocean. Eng. 23(3), 245ā259 (1998)
J.Ā Zhao, W.Ā Tao, H.Ā Zhang, K.Ā Yang, Study on side scan sonar image matching based on the integration of SURF and similarity calculation of typical areas, in OCEANS 2010 IEEE-Sydney (May 2010), pp. 1ā4
C.Ā Rominger, A.Ā Martin, A.Ā Khenchaf, H.Ā Laanaya, Sonar image registration based on conflict from the theory of belief functions, in Information Fusion, 2009. FUSIONā09. 12th International Conference on (July 2009), pp. 1317ā1324
M.T. Pham, D.Ā Gueriot, Guided block matching for sonar image registration using unsupervised Kohonen neural networks, in OCEANS 2013-San Diego: MTS/IEEE international conference (2013), pp. 1ā5
P.Y. Mignotte, M. Lianantonakis, Y. Petillot, Unsupervised registration of textured images: applications to side-scan 1, 622ā627 (2005)
C.Ā Chailloux, B.Ā Zerr, Non symbolic methods to register sonar images, in Oceans 2005-Europe, vol.Ā 1 (June 2005), pp. 276ā281
C.Ā Chailloux, Recalage dāimages sonar par appariement de rĆ©gions : application Ć la gĆ©nĆ©ration dāune mosaĆÆque, Ph.D. dissertation, UR1-UniversitĆ© de Rennes 1, ITIāDĆ©pt. Image et Traitement Information (Institut Mines-TĆ©lĆ©com-TĆ©lĆ©com Bretagne-UEB), 2007, th. doct. : Traitement du signal et tĆ©lĆ©communications, UniversitĆ© de Rennes 1, Institut Mines-TĆ©lĆ©com-TĆ©lĆ©com Bretagne-UEB (2007)
B.Ā Bonnett, M.Ā Hayes, Data-driven image registration for coherent change detection of synthetic aperture sonar imagery, in Proceedings of the 29th International Conference on Image and Vision Computing New Zealand, ser. IVCNZā14, (New York, NY, USA: ACM, 2014), pp. 196ā201. http://doi.acm.org/10.1145/2683405.2683455
P.Ā Viola, W.M. Wells, III, Alignment by maximization of mutual information. Int. J. Comput. Vision 24(2), 137ā154 (1997). http://dx.doi.org/10.1023/A:1007958904918
J.P.W. Pluim, J.B.A. Maintz, M.A. Viergever, Mutual-information-based registration of medical images: a survey. IEEE Trans. Med. Imaging, 986ā1004 (2003)
F.Ā Nicolas, B.Ā Zerr, A.Ā ArnoldĀ Bos, Sonar image registration: survey and experiments in a rigid context (2016)
D. Padfield, Masked object registration in the fourier domain. IEEE Trans. Image Process. 21(5), 2706ā2718 (2012)
D.Ā Ruprecht, H. Muller, Image warping with scattered data interpolation. IEEE Comput. Graph. Appl. 37ā43 (1995)
D.Ā Rueckert, L.Ā Sonoda, I.Ā Hayes, D.Ā Hill, M.Ā Leach, D.Ā Hawkes, Nonrigid registration using free-form deformations: Application to breast mr images 18(8), 712ā21, 08 (1999)
Z. Xie, G.E. Farin, Image registration using hierarchical b-splines. IEEE Trans. Vis. Comput. Graph. 10(1), 85ā94 (2004)
S.Ā Lee, G.Ā Wolberg, S.Y. Shin, Scattered data interpolation with multilevel b-splines. IEEE Trans. Vis. Comput. Graph. 3(3), 228ā244 (1997). http://dx.doi.org/10.1109/2945.620490
A.Ā Goshtasby, Piecewise cubic mapping functions for image registration. Pattern Recogn. 20(5), 525ā533 (1987) http://dx.doi.org/10.1016/0031-3203(87)90079-3
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
Ā© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Nicolas, F., Arnold-Bos, A., Quidu, I., Zerr, B. (2018). Fast Fourier-Based Block-Matching Algorithm for Sonar Tracks Registration in a Multiresolution Framework. In: Jaulin, L., et al. Marine Robotics and Applications. Ocean Engineering & Oceanography, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-70724-2_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-70724-2_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-70723-5
Online ISBN: 978-3-319-70724-2
eBook Packages: EngineeringEngineering (R0)