Skip to main content

Comparison of Different Methods to Fuse Theos Images

  • Conference paper
Advanced Data Mining and Applications (ADMA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6441))

Included in the following conference series:

  • 3016 Accesses

Abstract

Along with the development of the remote sensing, an increasing number of remote sensing applications such as land cover classification, feature detection, urban analysis, require both high spatial and high spectral resolution. On the other hand, the Satellite can’t get high spatial and high spectral resolution at the same time because of the incoming radiation energy to the sensor and the data volume collected by the sensor. Image fusion is an effective approach to integrate disparate and complementary information of multi-source image. As a new type of Remote Sensing data source, the lately launched Theos can be widely used in many applications. So the fusion of its high spatial resolution image and multi-spectral image is important. This paper selects several widely used methods for the fusion of data of high spatial resolution and high spectral resolution. The result of each approach is evaluated by qualitative and quantitative comparison and analysis.

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. Yun, Z.: Understanding Image Fusion. Photo Grammetric Engineering & Remote Sensing 7, 657–661 (2004)

    Google Scholar 

  2. Wald, L.: Some Terms of Reference in Data Fusion. IEEE Trans. Geosci. Remote Sens., 1190–1193 (1999)

    Google Scholar 

  3. Pohl, C., Genderen, J.L.: Multisensor Image Fusion in Remote Sensing: Concepts, Methods and Applications. International Journal of Remote Sensing 19(5), 823–854 (1998)

    Article  Google Scholar 

  4. Liu, J.G.: Smoothing filter-based intensity modulation: a spectral preserve image fusion technique for improving spatial details International J. Journal of Remote Sensing 18(21), 3461–3472 (2000)

    Article  Google Scholar 

  5. Wald, L., Ranchin, T., Mangolini, M.: Fusion of Satellite Images of Different Spatial Resolutions: Assessing The Quality of Resulting Images. Photogrammetric Engineering and Remote Sensing 63, 691–699 (1997)

    Google Scholar 

  6. Chavez, P.S., Sildes, S.C., Anderson, J.A.: Comparison of Three Different Methods to Merge Multiresolution and Multispectral Data: Landsat TM and SPOT Panchromatic. Photogrammetric Engineering and Remote Sensing 57, 295–303 (1991)

    Google Scholar 

  7. Liu, J.G.: Evaluation of Landsat-7 ETM+ Panchromatic Band for Image Fusion with Multispectal bands. Natural Resources Research 9(4), 269–276 (2000)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhang, S., He, G. (2010). Comparison of Different Methods to Fuse Theos Images. In: Cao, L., Zhong, J., Feng, Y. (eds) Advanced Data Mining and Applications. ADMA 2010. Lecture Notes in Computer Science(), vol 6441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17313-4_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-17313-4_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17312-7

  • Online ISBN: 978-3-642-17313-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics