In defense of iterated conditional mode for hyperspectral image classification

@article{Lin2014InDO,
  title={In defense of iterated conditional mode for hyperspectral image classification},
  author={Jianzhe Lin and Qi Wang and Yuan Yuan},
  journal={2014 IEEE International Conference on Multimedia and Expo (ICME)},
  year={2014},
  pages={1-6}
}
Hyperspectral image classification is one of the most significant topics in remote sensing. A large number of methods have been proposed to improve the classification accuracy. However, the improvement often comes at the cost of higher complexity. In this work, we mainly focus on the Markov Random Fields related paradigm, which involves a demanding energy minimization procedure. Traditional methods are prone to employ the advanced optimization techniques. On the contrary, this paper is in… CONTINUE READING
Highly Cited
This paper has 22 citations. REVIEW CITATIONS

References

Publications referenced by this paper.
Showing 1-10 of 10 references

A comparative study of energy minimization methods for markov random fields with smoothness-based priors

  • D. Scharstein O. Veksler V. Kolmogorov A. Agarwala M. Szeliski, R. Zabih, C. Rother
  • IEEE Trans. Pattern Analysis and Machine…
  • 2008
Highly Influential
3 Excerpts

A unified framework for map estimation in remote sensing image segmentation

  • F. Bovolo, L. Bruzzone
  • IEEE Trans. Pattern Analysis and Machine…
  • 2005
Highly Influential
3 Excerpts

A novel approach for spectral-spatial classification of hyperspectral data based on svm-mrf method

  • R. Rajabi M. Khodadadzadeh, H. Ghassemian
  • Proc. IEEE Int. Geoscience and Remote Sensing…
  • 2011
1 Excerpt

The spectral image processing system (sips)interactive visualization and analysis of imaging spectrometer data

  • J. B. Boardman K.B. Heidebrecht A.T. Shapiro P.J. Bar Kruse, A. B. Lefkoff, A.F.H. Goetz
  • Remote Sensing Environment, vol. 44, no. 2/3, pp…
  • 1993
2 Excerpts

Similar Papers

Loading similar papers…