Skip to main content

Abstract

In this contribution we analyze the problem of the fusion of time series of heterogeneous remote sensing images to serve classification and monitoring activities which can aid farming applications such as crop classification, change detection and monitoring. We propose several soft fusion operators that are based on different assumptions and model distinct desired properties. Conducted experiments on various geographic regions have been carried out and illustrate the effectiveness of our proposal.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Goshtasby, A.A., Nikolov, S.: Guest editorial: Image fusion: Advances in the state of the art. Inf. Fusion 8, 114–118 (2007)

    Article  Google Scholar 

  2. Pohl, C., Van Genderen, J.L.: Review article Multisensor image fusion in remote sensing: Concepts, methods and applications. Int. J. Remote Sens. 19, 823–854 (1998)

    Article  Google Scholar 

  3. Dammavalam, S.R.: Quality Assessment of Pixel-Level ImageFusion Using Fuzzy Logic. Int. J. Soft Comput. 3, 11–23 (2012)

    Article  Google Scholar 

  4. Zhao, L., Xu, B., Tang, W., Chen, Z.: A Pixel-Level Multisensor Image Fusion Algorithm Based on Fuzzy Logic. In: Wang, L., Jin, Y. (eds.) FSKD 2005. LNCS (LNAI), vol. 3613, pp. 717–720. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  5. Yager, R.R.: A framework for multi-source data fusion. Soft Comput. Data Min. 163, 175–200 (2004)

    Google Scholar 

  6. Le Maire, G., Marsden, C., Verhoef, W., Ponzoni, F.J., Lo Seen, D., Bégué, A., Stape, J.-L., Nouvellon, Y.: Leaf area index estimation with MODIS reflectance time series and model inversion during full rotations of Eucalyptus plantations. Remote Sens. Environ. 115, 586–599 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Bisquert, M., Bordogna, G., Boschetti, M., Poncelet, P., Teisseire, M. (2014). Soft Fusion of Heterogeneous Image Time Series. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2014. Communications in Computer and Information Science, vol 442. Springer, Cham. https://doi.org/10.1007/978-3-319-08795-5_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-08795-5_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08794-8

  • Online ISBN: 978-3-319-08795-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics