Change Detection Using High Spatial Resolution Remotely Sensed Imagery

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 180)

Abstract

This paper presents an evidence theory based change detection method capable of utilizing multiple image features.With a moving window, we first get the structural similarities of both time phase image visual features and construct the basic probability assignment function (BPAF) of D-S evidence theory. We then fuse all the evidence and get the changed image areas with decision rules. Comparative work on different experimental areas, combinations of change evidence and with other methods has been carried out. It shows that our method prevents effectively the detection errors from only utilizing single feature and thus improves the detection precision. Furthermore, since the image similarity is derived from image statistical features rather than original grey, texture and gradient features, this method is robust to low calibration precision.

Keywords

Evidence theory change detection high spatial resolution image multi-feature structural similarity 

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References

  1. 1.
    Bruzzone, L., Prieto, D.F.: Automatic analysis of the difference image for unsupervised change detection. IEEE Transactions on Geoscience and Remote Sensing 38(3), 1171–1182 (2000)CrossRefGoogle Scholar
  2. 2.
    Deng, W., Shao, X., Liu, H., Wan, G.: Discussion of remote sensing image classification. method based on evidence theory. Journal of Remote Sensing 11(4), 578–583 (2007)Google Scholar
  3. 3.
    Jacobs, I.S., Bean, C.P.: Fine particles, thin films and exchange anisotropy. In: Rado, G.T., Suhl, H. (eds.) Magnetism, vol. III, pp. 271–350. Academic, New York (1963)Google Scholar
  4. 4.
    Strunk Jr, W., White, E.: The elements of style, 3rd edn. Macmillan, NewYork (1980)Google Scholar
  5. 5.
    Nicole, R.: Title of paper with only first word capitalized. J. Name Stand. Abbrev. (in press)Google Scholar
  6. 6.
    Yorozu, Y., Hirano, M., Oka, K., Tagawa, Y.: Electron spectroscopy studies on magneto-optical media and plastic substrate interface. IEEE Transl. J. Magn. Japan 2, 740–741 (1987); Digests 9th Annual Conf. Magnetics Japan, p. 301 (1982)Google Scholar
  7. 7.
    Young, M.: The Technical Writer’s Handbook. University Science, Mill Valley (1989)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.School of Information Science and EngineeringWuhan University of Science and TechnologyWuhanChina
  2. 2.Experiment CenterAir Force Radar AcademyWuhanChina

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