Skip to main content
SpringerLink
Log in

Classification of multi-look polarimetric SAR imagery and polarization channel optimization

  • Published:
Journal of Electronics (China)

Abstract

In this paper, a new maximum likelihood (ML) classification algorithm is proposed to classify the multi-look polarimetric synthetic aperture radar (SAR) imagery. Experimental results with the NASA/JPL airborne L-band polarimetric SAR data demonstrate the effectiveness of the new algorithm. Furthermore, when using the algorithm in the classifications with subsets of the multi-look polarimetric SAR data, the polarization-channel optimization for the terrain type classification is implemented.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. H. Lim, A. A. Swartz, et al., Classification of earth terrain using polarimetric SAR images, J. of Geophysical Research, 94(1989)B6, 7049–7057.

    Google Scholar 

  2. G. De Grandi, G. Lemoine, A. Sieber, Supervised fully polarimetric classification: An experimental study on the Maestro-1 Freiburg data set, Proc. IGARSS’92, Huston, TX, USA: 1992, 782–785.

  3. J. A. Kong, A. A. Swartz, et al., Identification of terrain cover using the optimum polarimetric classifier, J. of Electromag. Waves and Appl., 2(1988)2, 171–194.

    Google Scholar 

  4. J. S. Lee, M. R. Gruns, Classification of multi-look polarimetric SAR imagery based on complex Wishart distribution, Int. J. Remote Sensing, 15(1994)11, 2299–2311.

    Article  Google Scholar 

  5. V. S. Frost, L. S. Yurovsky, Maximum likelihood classification of synthetic aperture radar imagery, Computer Vision, Graphic and Image Processing, 32(1985)2, 291–313.

    Article  Google Scholar 

  6. Q. Lin, J. P. Allebach, Combating speckle in SAR imagery: Vector filtering and sequential classification based on a multiplicative noise model, IEEE Trans. on GE, GE-28(1990)4, 674–653.

    Google Scholar 

  7. F. T. Ulaby, C. Elachi, (Ed.), Radar Polarimetry for Geoscience Application, MA: Artech House INC, 1990, Ch.2.

    Google Scholar 

  8. Liu Guoqing, Theoretical analysis and applications of polarimetric SAR imaging, Ph. D. Dissertation, Chengdu: Univ. of Electronic Science and Technology of China, 1996.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Electron. Eng., Univ. of Electron. Sci. & Tech. of China, 610054, Chengdu

    Liu Guoqing, Xiong Hong, Huang Shunji, A. Torre & F. Rubertone

  2. Dept. of Remote Sensing, Alenia Spazio SPA, 00131, Rome, Italy

    A. Torre & F. Rubertone

Authors
  1. Liu Guoqing
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiong Hong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Huang Shunji
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. A. Torre
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. F. Rubertone
    View author publications

    You can also search for this author in PubMed Google Scholar

Additional information

This work was performed at Alenia Spazio, Rome, Italy. It was a part of the cooperation project between Alenia Spazio and University of Electronic Science and Technology of China, Chengdu, China

About this article

Cite this article

Liu, G., Xiong, H., Huang, S. et al. Classification of multi-look polarimetric SAR imagery and polarization channel optimization. J. of Electron.(China) 15, 320–325 (1998). https://doi.org/10.1007/s11767-998-0005-z

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11767-998-0005-z

Key words

Search

Navigation