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Fuzzy Information and Engineering pp 846–851Cite as

Remote Sensing Image Classification Algorithm Based on Rough Set Theory

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Part of the book series: Advances in Soft Computing ((AINSC,volume 40))

Abstract

Rough sets theory is a relatively new soft computing tool to deal with vagueness and uncertainty. Considering the feature of remote sensing images and the basic theory and applications of rough sets, we put forward a remote sensing image classification algorithm based on rough set theory. In this article we first introduce the basic theory and character of rough sets and its applications in recent years are also pointed out. Then the theory of rough sets is introduced into the processing of remote image classify. Experiment research and classification effects are showed in this article about the new technology and it seems innovational and useful.

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References

  1. Pawlak, Z.: Rough sets. International Journal of Information and Computer Science 11, 341–356 (1982)

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Author information

Authors and Affiliations

  1. Guangdong Public Laboratory of Environmental Science and Technology, Guangzhou, 510650, P.R. China

    Guang-Jun Dong

  2. Information Engineering University Institute of Surveying and Mapping, Postfach 66, 450052 Zhengzhou,Email:topd@163.com, China

    Guang-Jun Dong, Yong-Sheng Zhang & Yong-Hong Fan

Authors
  1. Guang-Jun Dong
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  2. Yong-Sheng Zhang
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  3. Yong-Hong Fan
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Editor information

Bing-Yuan Cao

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© 2007 Springer-Verlag Berlin Heidelberg

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Cite this paper

Dong, GJ., Zhang, YS., Fan, YH. (2007). Remote Sensing Image Classification Algorithm Based on Rough Set Theory. In: Cao, BY. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71441-5_92

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  • DOI: https://doi.org/10.1007/978-3-540-71441-5_92

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71440-8

  • Online ISBN: 978-3-540-71441-5

  • eBook Packages: EngineeringEngineering (R0)

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