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A Gaussian-Rayleigh mixture modeling approach for through-the-wall radar image segmentation

Conference Paper


Abstract


  • In this paper, we propose a Gausssian-Rayleigh mixture modeling approach to segment indoor radar images in urban sensing applications. The performance of the proposed method is evaluated on real 2D polarimetric data. Experimental results show that the proposed method enhances image quality by distinguishing between target and clutter regions. The proposed method is also compared to an existing Neyman-Pearson (NP) target detector that has been recently devised for through-the-wall radar imaging. Performance evaluation of both methods shows that the proposed method outperforms the NP detector in enhancing the input images. © 2012 IEEE.

Authors


  •   Seng, C H. (external author)
  •   Bouzerdoum, Salim
  •   Amin, Moeness G. (external author)
  •   Ahmad, F (external author)

Publication Date


  • 2012

Citation


  • C. H. Seng, A. Bouzerdoum, M. G. Amin & F. Ahmad, "A Gaussian-Rayleigh mixture modeling approach for through-the-wall radar image segmentation," in ICASSP 2012: IEEE International Conference on Acoustics, Speech and Signal Processing, 2012, pp. 877-880.

Scopus Eid


  • 2-s2.0-84867615899

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/2223

Has Global Citation Frequency


Start Page


  • 877

End Page


  • 880

Place Of Publication


  • USA

Abstract


  • In this paper, we propose a Gausssian-Rayleigh mixture modeling approach to segment indoor radar images in urban sensing applications. The performance of the proposed method is evaluated on real 2D polarimetric data. Experimental results show that the proposed method enhances image quality by distinguishing between target and clutter regions. The proposed method is also compared to an existing Neyman-Pearson (NP) target detector that has been recently devised for through-the-wall radar imaging. Performance evaluation of both methods shows that the proposed method outperforms the NP detector in enhancing the input images. © 2012 IEEE.

Authors


  •   Seng, C H. (external author)
  •   Bouzerdoum, Salim
  •   Amin, Moeness G. (external author)
  •   Ahmad, F (external author)

Publication Date


  • 2012

Citation


  • C. H. Seng, A. Bouzerdoum, M. G. Amin & F. Ahmad, "A Gaussian-Rayleigh mixture modeling approach for through-the-wall radar image segmentation," in ICASSP 2012: IEEE International Conference on Acoustics, Speech and Signal Processing, 2012, pp. 877-880.

Scopus Eid


  • 2-s2.0-84867615899

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/2223

Has Global Citation Frequency


Start Page


  • 877

End Page


  • 880

Place Of Publication


  • USA