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Multi-image Fusion in Remote Sensing: Spatial Enhancement vs. Spectral Characteristics Preservation

  • Conference paper
Advances in Visual Computing (ISVC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5359))

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Abstract

In remote sensing, image fusion techniques are used to fuse high spatial resolution panchromatic and lower spatial resolution multispectral images that are simultaneously recorded by one sensor. This is done to create high resolution multispectral image datasets (pansharpening). In most cases, these techniques provide very good results, i.e. they retain the high spatial resolution of the panchromatic image and the spectral information from the multispectral image. When applied to multitemporal and/or multisensoral image data, these techniques still create spatially enhanced datasets but usually at the expense of the spectral characteristics. In this study, eight multitemporal remote sensing images are fused with one panchromatic image to test eight different fusion techniques. The fused images are visually and quantitatively analyzed for spectral characteristics preservation and spatial enhancement. Of the employed methods, only the newly developed Ehlers fusion guarantees excellent color preservation and spatial improvement for all dates and sensors.

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Author information

Authors and Affiliations

  1. Institute for Geoinformatics and Remote Sensing, University of Osnabrueck, Seminarstr. 19 a/b, D-49074, Osnabrueck, Germany

    Manfred Ehlers

Authors
  1. Manfred Ehlers
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Digital Image Research Center, Kingston University, London, UK

    Paolo Remagnino

  6. Mitsubishi Electric Research Laboratories, P.O. Box 02139, Cambridge, MA, USA

    Fatih Porikli

  7. Computer and Information Science and Engineering, University of Florida, P.O. Box, FL 32611-6120, Gainsville, USA

    Jörg Peters

  8. IBM T.J. Watson Research Center, 19 Skyline Drive, NY 10532, Hawthorne, USA

    James Klosowski

  9. 128 Memorial Mall, Stewart B001, IN 47907, West Lafayette, USA

    Laura Arns

  10. Denver Museum of Nature and Space, 2001 Colorade Blvd. Denver,, CO 80205, USA

    Yu Ka Chun

  11. Departmen of Computer Science,, NC State University, Campus Box 8206, NC 27695-8206, Raleigh, USA

    Theresa-Marie Rhyne

  12. Los Alamos National Labs, P.O. Box 1663, NM 87545, Los Alamos, USA

    Laura Monroe

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© 2008 Springer-Verlag Berlin Heidelberg

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Ehlers, M. (2008). Multi-image Fusion in Remote Sensing: Spatial Enhancement vs. Spectral Characteristics Preservation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89646-3_8

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  • DOI: https://doi.org/10.1007/978-3-540-89646-3_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89645-6

  • Online ISBN: 978-3-540-89646-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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