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Consistent image alignment for video mosaicing

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Abstract

Image mosaicing is widely used in computer vision applications. In this paper, a new globally consistent image alignment method for video mosaicing is presented. Due to various uncertainties on noise, illumination, and modeling, the problem of global image alignment is considered as a stochastic estimation problem. The augmented system state consists of the transformation parameters of video image sequences. The system motion model, the augmentation model, and the observation model are constructed. The homography parameters of image sequences are augmented and estimated recursively with augmented Kalman filter in a common state vector and covariance matrix. Some experimental results are provided to validate the performance of the proposed method. The proposed image alignment method can handle the uncertainty efficiently. Image alignment is globally consistent and accurate.

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References

  1. Helmer E.H., Ruefenacht B.: Cloud-free satellite image mosaics with regression trees and histogram matching. Photogrammetr. Eng. Remote Sens. 71(9), 1079–1089 (2005)

    Google Scholar 

  2. Hu, R., Shi, R., Shen, I.F., Chen, W.: Video stabilization using scale-invariant features. In: Proceedings of 11th International Conference on Information Visualization, Zurich, Switzerland, pp. 871–877, July 04–06 (2007)

  3. Gracias, X., Negahdaripour, S.: Underwater mosaic creation using video sequences from different altitudes. In: Proceedings of IEEE Conference on OCEANS’05, Washington, DC, pp. 1295–1300, Sept. 17–23 (2005)

  4. Leung, W.H., Chen, T.: Compression with mosaic prediction for image-based rendering applications. In: Proceedings of IEEE International Conference on Multimedia and Expo, New York, USA, pp. 1649–1652, July 30–August 2 (2000)

  5. Irani M., Anandan P.: Video indexing based on mosaic representations. Proc. IEEE 86(5), 905–921 (1998)

    Article  Google Scholar 

  6. Elad M., Feuer A.: Super-resolution reconstruction of image sequences. IEEE Trans. Pattern Anal. Mach. Intell. 21(9), 817–834 (1999)

    Article  Google Scholar 

  7. Capel D.P.: Image Mosaicing and Super-resolution, pp. 21–67. Springer, Berlin (2004)

    Book  MATH  Google Scholar 

  8. Fedorov, D., Fonseca, L.M., Kenney, C., Manjunath, B.S.: Automatic registration and mosaicking system for remotely sensed imagery. In: Proceedings of SPIE 9th International Symposium on Remote Sensing, Crete, Greece, Sept. 24–27, pp. 444–451 (2002)

  9. Brown, M., Lowe, D.G.: Recognising panoramas. In: Proceedings of 9th International Conference on Computer Vision, Nice, France, Oct. 13–16, pp. 1218–1225 (2003)

  10. Zitova B., Flusser J.: Image registration methods: A survey. Image Vis. Comput. 21(11), 977–1000 (2003)

    Article  Google Scholar 

  11. Chiba N., Kano H., Minoh M., Yasuda M.: Feature-based image mosaicing. Syst. Comput. Jpn. 31(7), 1–9 (2000)

    Article  Google Scholar 

  12. Song, W., Wang, H.: Feature based image registration and mosaicing. In: Proceedings of SPIE International Conference on AeroSense, Orlando, USA, Apr. 24–28, pp. 260–268 (2000)

  13. Kahl F., Agarwal S., Chandraker M., Kriegman D., Belongie S.: Practical global optimization for multiview geometry. Int. J. Comput. Vis. 79(3), 271–284 (2008)

    Article  Google Scholar 

  14. Hsieh J.W.: Fast stitching algorithm for moving object detection and mosaic construction. Image Vis. Comput. 22(4), 291–306 (2004)

    Article  Google Scholar 

  15. Triggs, B., McLauchlan, P.F., Hartley, R.I., Fitzgibbon, A.W.: Bundle adjustment—A modern synthesis. In: Proceedings of ICCV Workshop on Vision Algorithms, Corfu, Greece, Sept. 21–22, pp. 298–372 (1999)

  16. Can A., Stewart C.V., Roysam B., Tanenbaum H.L.: A feature-based technique for joint linear estimation of high-order image-to-mosaic transformations: Mosaicing the curved human retina. IEEE Trans. Pattern Anal. Mach. Intell. 24(3), 412–419 (2002)

    Article  Google Scholar 

  17. Cervantes, A., Kang, E.Y.: Progressive multi-image registration based on feature tracking. In: Proceedings of International Conference on Image Processing, Computer Vision and Pattern Recognition, Las Vegas, USA, June 26–29, pp. 633–639 (2006)

  18. Kang, E.Y., Cohen, I., Medioni, G.: A graph-based global registration for 2D mosaics. In: Proceedings of 15th International Conference on Pattern Recognition, Barcelrona, Spain, Sept. 3–7, pp. 257–260 (2000)

  19. Zhang, P.E., Milios, E., Gu, J.: Graph-based automatic consistent image mosaicking. In: Proceeedings of IEEE International Conference on Robotics and Biomimetics, Shenyang, China, Aug. 22–25, pp. 558–563 (2004)

  20. Caballero, F., Merino, L., Ferruz, J., Ollero, A.: Homography based Kalman filter for mosaic building. Applications to UAV position estimation. In: Proceedings of IEEE International Conference on Robotics and Automation, Roma, Italy, Apr. 10–14, pp. 2004–2009 (2007)

  21. Garcia, R., Puig, J., Ridao, P., Cufí, X.: Augmented state Kalman filtering for AUV navigation. In: Proceedings of IEEE International Conference on Robotics and Automation, Washington, USA, May 11–15, pp. 4010–4015 (2002)

  22. Durrant-whyte H., Bailey T.: Simultaneous localization and mapping (SLAM): Part I The essential algorithms. Robot. Automat. Mag. 13(2), 99–110 (2006)

    Article  Google Scholar 

  23. Civera J., Davison A.J., Magallón J.A., Montiel J.M.M.: Drift-free real-time sequential mosaicing. Int. J. Comput. Vis. 81(2), 128–137 (2009)

    Article  Google Scholar 

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Authors and Affiliations

  1. Changzhou Key Laboratory of Software Technology and Application, Changzhou Institute of Technology, Changzhou, China

    Zezhong Xu

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  1. Zezhong Xu
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Correspondence to Zezhong Xu.

Additional information

This work was supported in part by the Natural Science Foundation of the Jiangsu Higher Education Institutions (08KJD520002) and QingLan Project of Jiangsu Province.

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Xu, Z. Consistent image alignment for video mosaicing. SIViP 7, 129–135 (2013). https://doi.org/10.1007/s11760-011-0212-1

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  • DOI: https://doi.org/10.1007/s11760-011-0212-1

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