13 August 1999 Target matching in synthetic aperture radar imagery using a nonlinear optimization technique
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Recognition of targets in synthetic aperture radar (SAR) imagery is approached from the viewpoint of an optimization problem. Features are extracted from SAR target images and are treated as point sets. The matching problem is formulated as a non-linear objective function to maximize the number of matched features and minimize the distance between features. The minimum of this function is found using a deterministic annealing process. Registration is performed iteratively by using an analytically computed minimum at each temperature of the annealing. Thus, the images do not need to be initially registered as any translational error between them is solved for as part of the optimization. We have also extended the initial objective function to incorporate multiple feature classes. This matching method is robust to spurious, missing and migrating features. Matching results are presented for simulated XPATCH and real MSTAR SAR target imagery demonstrating the utility of this approach.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Reuven Meth, Rama Chellappa, "Target matching in synthetic aperture radar imagery using a nonlinear optimization technique", Proc. SPIE 3721, Algorithms for Synthetic Aperture Radar Imagery VI, (13 August 1999); doi: 10.1117/12.357669; https://doi.org/10.1117/12.357669

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