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Probabilistic fuzzy image fusion approach for radar through wall sensing

Journal Article


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Abstract


  • This paper addresses the problem of combining multiple radar images of the same scene to produce a more informative composite image. The proposed approach for probabilistic fuzzy logic-based image fusion automatically forms fuzzy membership functions using the Gaussian–Rayleigh mixture distribution. It fuses the input pixel values directly without requiring fuzzification and defuzzification, thereby removing the subjective nature of the existing fuzzy logic methods. In this paper, the proposed approach is applied to through-the-wall radar imaging in urban sensing and evaluated on real multiview and polarimetric data. Experimental results show that the proposed approach yields improved image contrast and enhances target detection.

Publication Date


  • 2013

Citation


  • C. Hau. Seng, A. Bouzerdoum, M. G.. Amin & S. Lam. Phung, "Probabilistic fuzzy image fusion approach for radar through wall sensing," IEEE Transactions on Image Processing, vol. 22, (12) pp. 4938-4951, 2013.

Scopus Eid


  • 2-s2.0-84885144653

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=2422&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1413

Has Global Citation Frequency


Number Of Pages


  • 13

Start Page


  • 4938

End Page


  • 4951

Volume


  • 22

Issue


  • 12

Place Of Publication


  • United States

Abstract


  • This paper addresses the problem of combining multiple radar images of the same scene to produce a more informative composite image. The proposed approach for probabilistic fuzzy logic-based image fusion automatically forms fuzzy membership functions using the Gaussian–Rayleigh mixture distribution. It fuses the input pixel values directly without requiring fuzzification and defuzzification, thereby removing the subjective nature of the existing fuzzy logic methods. In this paper, the proposed approach is applied to through-the-wall radar imaging in urban sensing and evaluated on real multiview and polarimetric data. Experimental results show that the proposed approach yields improved image contrast and enhances target detection.

Publication Date


  • 2013

Citation


  • C. Hau. Seng, A. Bouzerdoum, M. G.. Amin & S. Lam. Phung, "Probabilistic fuzzy image fusion approach for radar through wall sensing," IEEE Transactions on Image Processing, vol. 22, (12) pp. 4938-4951, 2013.

Scopus Eid


  • 2-s2.0-84885144653

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=2422&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1413

Has Global Citation Frequency


Number Of Pages


  • 13

Start Page


  • 4938

End Page


  • 4951

Volume


  • 22

Issue


  • 12

Place Of Publication


  • United States