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Article information
2018 , Volume 23, ¹ 1, p.61-72
Kamaev A.N., Smagin S.I.
Image stitching for construction of seabed mosaics
Purpose. Seabed mosaics are built of tens of thousands of images obtained by the AUV at a small distance from the bottom. The height of the survey is limited by the power of the AUV lighting equipment and the transparency of the water and is often comparable with the differences in the heights of the bottom. This leads to strong distortions caused by parallax, which makes standard stitching methods inapplicable to the construction of photographic maps of the bottom with a complex relief. Methodology. The article proposes to consider the problem of constructing seabed mosaics as a problem of 3D reconstruction. Two approaches to stitching images are described: simple stitching and based on a 3D bottom model. With simple stitching, the relief represented by each image is approximated by a plane that is then projected onto the common plane of the seabed mosaic. When stitching based on a 3D model, the bottom section model is first constructed using the Delaunay triangulation, and then each triangle of the model is projected onto the plane of the map using a graphic accelerator GPU. To mix colors, a simple method of weighting the pixels of images is used, depending on their distance from the edges of the image. Findings. Stitching algorithms proposed in the paper were tested on images obtained by both real AUV and synthetic images. This allowed us to verify efficiency of stitching algorithms for conditions of a highly complex relief. In combination with simple color blending techniques, proposed algorithms have shown their practical efficiency. The stitching algorithm, based on the 3D model demonstrated its robustness to distortions caused by parallax. Originality/value. The main advantage of described approach is an absence of necessity to use computationally consuming, nontrivial color blending techniques while constructing seabed mosaics in the case of complex bottom relief.
[full text]
Keywords: image stitching, bundle adjustment, AUV, seabed mosaic, 3D model
doi: 10.5072/ICT.2018.1.11926
Author(s):
Kamaev Aleksandr Nikolaevich
PhD.
Position: Research Scientist
Office: Computing Center FEB RAS
Address: 680000, Russia, Khabarovsk
Phone Office: (4212)227267
Smagin Sergey Ivanovich
Dr. , Correspondent member of RAS, Professor
Position: Director
Office: Computer Center FEB RAS
Address: 680000, Russia, Khabarovsk
Phone Office: (4212) 22 72 67
E-mail: smagin@ccfebras.ru
SPIN-code: 2419-4990 References:
[1] Prados, R., Garcia, R., Gracias, N., Escartin, J., Neumann, L. A novel blending technique for underwater giga-mosaicing. IEEE International Jour-nal of Oceanic Engineering. 2012; 37(4):626–644.
[2] Prados, R., Garcia, R., Neumann, L. Image blending techniques and their application in under-water mosaicing. Springer; 2014: 107. ISBN: 3319055577.
[3] Elibol, A., Gracias, N., Garcia, R. Efficient topology estimation for large scale optical mapping. Springer Tracts in Advanced Robotics. 2013; (82):88.
[4] Hartley, R., Zisserman, A. Multiple view geometry in computer vision. Cambridge University Press; 2004: 673. ISBN: 978-0-521-54051-3.
[5] Szeliski, R. Computer vision. Algorithms and applications. Series Title: Texts in Computer Science. Springer-Verlag London; 2011: 812.
[6] Kamaev, A.N. Investigation of algorithms for ordering the coefficients of systems of linear algebraic equations in computer vision problems. Information Science and Control Systems’. 2013; 3(37):32–44. (In Russ.)
[7] Kamaev, A.N. Seabed mosaics creation based on large images arrays. Proc. of the Intern. Conf. “GraphiCon’2013”. Vladivostok; 2013: 298–301. (In Russ.)
[8] Barber, C.B., Dobkin, D.P., Huhdanpaa, H. The quickhull algorithm for convex hulls. Acm transactions on mathematical software. 1996; 22(4):469–483.
[9] Skvortsov, A.V. Triangulyatsiya Delone i ee primenenie [Delaunay triangulation and its application]. Tomsk: Izdatel'stvo TGU; 2002: 128. ( In Russ.)
[10] Chen, C.-Y., Klette, R. Image stitching — comparisons and new techniques. Proc. of the Computer Analysis of Images and Patterns. Ljubljana; 1999:615–622.
[11] Uyttendaele, M., Eden, A., Szeliski, R. Eliminating ghosting and exposure artifacts in image mosaics. Proc. of the IEEE Computer Society Conference on CVPR. Kauai; 2001:509–516.
[12] Lagae, A., Lefebvre, S., Cook, R., DeRose, T., Drettakis, G., Ebert, D. S., Lewis, J.P., Perlin, K., Zwicker, M. A survey of procedural noise functions. Computer Graphics Forum. 2010; 29(8):2579–2600.
Bibliography link:
Kamaev A.N., Smagin S.I. Image stitching for construction of seabed mosaics // Computational technologies. 2018. V. 23. ¹ 1. P. 61-72
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