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http://dx.doi.org/10.9766/KIMST.2022.25.5.462

Similarity Analysis Between SAR Target Images Based on Siamese Network  

Park, Ji-Hoon (Defense AI Technology Center, Agency for Defense Development)
Publication Information
Journal of the Korea Institute of Military Science and Technology / v.25, no.5, 2022 , pp. 462-475 More about this Journal
Abstract
Different from the field of electro-optical(EO) image analysis, there has been less interest in similarity metrics between synthetic aperture radar(SAR) target images. A reliable and objective similarity analysis for SAR target images is expected to enable the verification of the SAR measurement process or provide the guidelines of target CAD modeling that can be used for simulating realistic SAR target images. For this purpose, this paper presents a similarity analysis method based on the siamese network that quantifies the subjective assessment through the distance learning of similar and dissimilar SAR target image pairs. The proposed method is applied to MSTAR SAR target images of slightly different depression angles and the resultant metrics are compared and analyzed with qualitative evaluation. Since the image similarity is somewhat related to recognition performance, the capacity of the proposed method for target recognition is further checked experimentally with the confusion matrix.
Keywords
Synthetic Aperture Radar; SAR Target Image; Similarity Analysis; Siamese Network; Deep Learning;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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