Target recognition in synthetic aperture radar images using binary morphological operations

Baiyuan Ding; Gongjian Wen; Conghui Ma; Xiaoliang Yang

doi:10.1117/1.JRS.10.046006

19 October 2016 Target recognition in synthetic aperture radar images using binary morphological operations

Baiyuan Ding, Gongjian Wen, Conghui Ma, Xiaoliang Yang

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 10, Issue 4, 046006 (October 2016). https://doi.org/10.1117/1.JRS.10.046006

Abstract

Feature extraction and matching are two important steps in synthetic aperture radar automatic target recognition. This paper uses the binary target region as the feature and proposes a matching scheme for the target regions using binary morphological operations. The residuals between the testing target region and its corresponding template target regions are processed by the morphological opening operation. Then, a similarity measure is defined based on the residual remains to evaluate the similarities between different targets. Afterward, a Bayesian decision fusion is employed to fuse the similarities gained by different structuring elements to further enhance the recognition performance. The nonlinearity of the opening operation as well as the Bayesian decision fusion makes the proposed method robust to the nonlinear deformations of the target region. Experimental results on the moving and stationary target acquisition and recognition dataset demonstrate the validity of the proposed method.

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Baiyuan Ding, Gongjian Wen, Conghui Ma, and Xiaoliang Yang "Target recognition in synthetic aperture radar images using binary morphological operations," Journal of Applied Remote Sensing 10(4), 046006 (19 October 2016). https://doi.org/10.1117/1.JRS.10.046006

Published: 19 October 2016

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