doi:

DOI: 10.3724/SP.J.1004.2013.02051

Acta Automatica Sinica (自动化学报) 2013/39:12 PP.2051-2063

A High Performance Edge Point Feature Match Method of SAR Images


Abstract:
A precise, e±cient and robust edge point set matching method of synthetic aperture radar (SAR) image is presented. First, the adaptability of the affine transform model used in the remote sensing image matching is analyzed, and the parameters of the a±ne transform model are decomposed. Next, a modified ratio of exponentially weighted averages (ROEWA) edge detector is used to get the strength and direction of each edge point with the eight directional templates, the matching similarity criterion and the joint similarity-square summation joint feature (SSJF) are constructed based on the strength and direction of the edge point in images. Then, parameters of the transform model between the matching SAR images are determined with the modified genetic algorithms (GA) which is used to obtain the global optimum extremum of the joint similarity. Finally, the performance of the method is analyzed in theory and validated with SAR images matching experiments.

Key words:Synthetic aperture radar (SAR) images matching, affine transform model, parameters decomposition, pixel migration, joint similarity, genetic algorithm (GA)

ReleaseDate:2014-07-21 17:04:34

Funds:National Natural Science Foundation of China (61002023)



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