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Journal of Applied Remote Sensing

Automatic target recognition scheme for a high-resolution and large-scale synthetic aperture radar image
Author(s): Song Tu; Yi Su; Wei Wang; Boli Xiong; Yu Li
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Paper Abstract

Existing automatic target recognition of synthetic aperture radar (SAR ATR) schemes mainly focus on target chips, but there is very little research for a large-scale and high-resolution SAR image that is more practical for SAR image interpretation. How to recognize targets efficiently and accurately from a large-scale and high-resolution SAR image is still a challenge. We present a scheme based on the combination of a salient detection approach, an active contour model (ACM), an affine-invariant shape descriptor, and the corresponding shape context. During the detection stage, the spectral residual approach is utilized to efficiently preselect salient regions. The proposed convex ACM, based on a ratio distance and distribution metric which makes it more robust to multiplicative speckled noise, is then adopted to get accurate candidate target chips. For the discrimination stage, a cumulative sum of multiscale lacunarity feature is proposed to select vehicle chips from clutter chips. Finally, affine-invariant shape features, obtained from the contours by our proposed ACM, are combined with a corresponding shape context to make the classification more accurate. Experimental results demonstrate that our SAR ATR system, integrating all the proposed methods, is feasible in ATR from a high-resolution and large-scale SAR image.

Paper Details

Date Published: 11 June 2015
PDF: 34 pages
J. Appl. Remote Sens. 9(1) 096039 doi: 10.1117/1.JRS.9.096039
Published in: Journal of Applied Remote Sensing Volume 9, Issue 1
Show Author Affiliations
Song Tu, National Univ. of Defense Technology (China)
Yi Su, National Univ. of Defense Technology (China)
Wei Wang, National Univ. of Defense Technology (China)
Boli Xiong, National Univ. of Defense Technology (China)
Yu Li, National Univ. of Defense Technology (China)


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