8 March 2018 Efficient moving target analysis for inverse synthetic aperture radar images via joint speeded-up robust features and regular moment
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Abstract
We propose a moving target analysis algorithm using speeded-up robust features (SURF) and regular moment in inverse synthetic aperture radar (ISAR) image sequences. In our study, we first extract interest points from ISAR image sequences by SURF. Different from traditional feature point extraction methods, SURF-based feature points are invariant to scattering intensity, target rotation, and image size. Then, we employ a bilateral feature registering model to match these feature points. The feature registering scheme can not only search the isotropic feature points to link the image sequences but also reduce the error matching pairs. After that, the target centroid is detected by regular moment. Consequently, a cost function based on correlation coefficient is adopted to analyze the motion information. Experimental results based on simulated and real data validate the effectiveness and practicability of the proposed method.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Hongxin Yang, Hongxin Yang, Fulin Su, Fulin Su, } "Efficient moving target analysis for inverse synthetic aperture radar images via joint speeded-up robust features and regular moment," Journal of Applied Remote Sensing 12(1), 015019 (8 March 2018). https://doi.org/10.1117/1.JRS.12.015019 . Submission: Received: 25 July 2017; Accepted: 19 February 2018
Received: 25 July 2017; Accepted: 19 February 2018; Published: 8 March 2018
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