Title
A Gaussian-Rayleigh mixture modeling approach for through-the-wall radar image segmentation
Document Type
Conference Paper
RIS ID
69526
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.
This record is in the process of being updated. Please contact us for more information.
Publication Details
C. 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.