Skip to main content
Springer Nature Link
Log in

Computationally Efficient Image Mosaicing Using Spanning Tree Representations

  • Conference paper
Advances in Informatics (PCI 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3746))

Included in the following conference series:

Abstract

Optimal image mosaicing has large computational complexity, that becomes prohibitive as the number of sub-images increases. Two methods are proposed, which require less computation time by performing mosaicing in pairs of two sub-images at a time, without significant reconstruction losses, as evidenced by simulation results.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Swarnakar, V., Jeong, M., Wasserman, R., Andres, E., Wobschall, D.: Integrated distortion correction and reconstruction technique for digital mosaic mammography. In: Proc. SPIE Medical Imaging 1997: Image Display, vol. 3031, pp. 673–681 (1997)

    Google Scholar 

  2. Shum, H.-Y., Szelisky, R.: Construction of Panoramic Image Mosaics with Global and Local Alignment. International Journal of Computer Vision 36(2), 101–130 (2000)

    Article  Google Scholar 

  3. Sawhney, H.S., Kumar, R.: True multi-image alignment and its application to mosaicing and lens distortion. In: Proc. CVPR 1997, pp. 450–456 (1997)

    Google Scholar 

  4. Puech, W., Bors, A.G., Pitas, I., Chassery, J.-M.: Projection distortion analysis for flattened image mosaicing from straight uniform generalized cylinders. Pattern Recognition 34(8), 1657–1670 (2001)

    Article  MATH  Google Scholar 

  5. Peleg, S., Herman, J.: Panoramic Mosaics with VideoBrush. In: Proc IUW 1997, May 1997, pp. 261–264 (1997)

    Google Scholar 

  6. Netravali, A.N., Haskell, B.G.: Digital Pictures: Representation and Compression. Plenum Press (1988)

    Google Scholar 

  7. Biggs, N.L., Lloyd, E.K., Wilson, R.J.: Graph Theory, pp. 1736–1936. Clarendon Press (1986)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Artificial Intelligence and Information Analysis Laboratory, Department of Informatics, Aristotle University of Thessaloniki, GR-54124, Thessaloniki, Greece

    Nikos Nikolaidis & Ioannis Pitas

Authors
  1. Nikos Nikolaidis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ioannis Pitas
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer and Communication Engineering, University of Thessaly, Glavani 37, 382 21, Volos, Greece

    Panayiotis Bozanis

  2. Department of Computer and Communication Engineering, University of Thessaly, 382 21, Volos, Greece

    Elias N. Houstis

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Nikolaidis, N., Pitas, I. (2005). Computationally Efficient Image Mosaicing Using Spanning Tree Representations. In: Bozanis, P., Houstis, E.N. (eds) Advances in Informatics. PCI 2005. Lecture Notes in Computer Science, vol 3746. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11573036_68

Download citation

  • DOI: https://doi.org/10.1007/11573036_68

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29673-7

  • Online ISBN: 978-3-540-32091-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics