Side-scan sonar image registration for AUV navigation

The ability of an AUV to navigate an underwater environment precisely and for an extended period depends on its effectiveness at making accurate observations regarding its location and orientation. An AUV platform equipped with a side-scan sonar system has the potential to register the current sonar image with previously captured images for the purpose of obtaining information about the vehicle's pose. Image registration is a procedure which transforms images viewed from different perspectives into a single coordinate system. The significance of using image registration techniques in a surveying or monitoring context comes from the fact that the registration parameters could provide the AUV with an indication of the discrepancy between its expected and observed pose vectors. As such, image registration provides feedback which can be used to compensate for drift in inertial sensors or to provide a standalone navigation solution in the event that the inertial navigation system fails. In order for image registration to provide an effective means for feedback a number of requirements on the performance of the image registration method employed must be met. Not only must the method be accurate in the face of possible image variations, but it must operate in real-time using the limited computing resources available within an AUV. In this paper, a number of key image registration techniques are applied to side-scan sonar images. These techniques include those based on the maximization of mutual information, log-polar cross-correlation, the Scale-Invariant Feature Transform (SIFT), and phase correlation. The performance of these techniques is assessed based on a number of metrics including execution time and registration accuracy. The challenges introduced by side-scan sonar imaging systems which degrade the performance of image registration are also discussed in detail.

[1]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[2]  B. Zerr,et al.  Non symbolic methods to register SONAR images , 2005, Europe Oceans 2005.

[3]  Max A. Viergever,et al.  Mutual-information-based registration of medical images: a survey , 2003, IEEE Transactions on Medical Imaging.

[4]  C. Chailloux Region of Interest on SONAR Image for Non Symbolic Registration , 2005, Proceedings of OCEANS 2005 MTS/IEEE.

[5]  C. Morandi,et al.  Registration of Translated and Rotated Images Using Finite Fourier Transforms , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  George Wolberg,et al.  Robust image registration using log-polar transform , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[7]  Paul A. Viola,et al.  Alignment by Maximization of Mutual Information , 1995, Proceedings of IEEE International Conference on Computer Vision.

[8]  H. Bleuler,et al.  Terrain-based navigation for underwater vehicles using side scan sonar images , 2008, OCEANS 2008.

[9]  Guy Marchal,et al.  Multimodality image registration by maximization of mutual information , 1997, IEEE Transactions on Medical Imaging.

[10]  Alan V. Oppenheim,et al.  Geometric distortions in side-scan sonar images: a procedure for their estimation and correction , 1992 .

[11]  Jan Flusser,et al.  Image registration methods: a survey , 2003, Image Vis. Comput..

[12]  M. Lianantonakis,et al.  Sidescan sonar segmentation using active contours and level set methods , 2005, Europe Oceans 2005.

[13]  Jeff Smith,et al.  Autonomous Underwater Vehicle Navigation , 1995 .

[14]  Christian Roux,et al.  Side-scan sonar image matching , 1998 .

[15]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[16]  B. N. Chatterji,et al.  An FFT-based technique for translation, rotation, and scale-invariant image registration , 1996, IEEE Trans. Image Process..

[17]  C. D. Kuglin,et al.  The phase correlation image alignment method , 1975 .